[Decoding Chatgpt] Yang Qingfeng | Chatgpt: Characteristic Analysis and Ethical Investigation

Since November 2022, ChatGPT, a chat robot developed by American artificial intelligence research company OpenAI, has quickly become the fastest-growing consumer-grade application in history, attracting widespread attention. The emergence of ChatGPT has become the tipping point of the development of artificial intelligence, which has promoted the competition of scientific and technological innovation in various countries to enter a new track. The leap of technology will inevitably lead to in-depth observation in application scenarios. No matter how smart artificial intelligence services become, adapting to and meeting the needs of human development is always the fundamental direction. Facing the future, discussing ChatGPT’s important influence on people’s mode of production, lifestyle, way of thinking, behavior mode, values, industrial revolution and academic research will help us to use and manage this technology correctly and then think about the development prospect of artificial intelligence.

Hegel mentioned the concept of bubble burst in the Ethical System, which meant that the process of destruction was like an expanding bubble bursting into countless tiny water droplets. If we look at the development of artificial intelligence technology with this concept, we will find that it is more consistent. After the artificial intelligence bubble burst in 1956, it became many tiny water droplets and splashed everywhere. There are AlphaGo and so on in chess; There are AlphaFold and so on in scientific research; Language dialogue includes LaMDA, ChatGPT, etc. Image generation includes Discord, Midjourney and so on. These technologies have gradually converged into a force, which has involved mankind in an era of intelligent generation.

ChatGPT: generating and embedding

Generation constitutes the first feature of ChatGPT, which means innovation, but this is questioned. Chomsky believes that ChatGPT discovers rules from massive data, and then connects the data according to the rules to form similar content written by people, and thinks that ChatGPT is a plagiarism tool. This view is somewhat inaccurate. In the process of ChatGPT generation, something new is produced. However, this is not new in the sense of existence, that is to say, it does not produce new objects, but finds unseen objects from old things through attention mechanism. In this sense, it belongs to the new in the sense of attention. In 2017, a paper entitled "Attention is All You Need" proposed transformer based on the concept of attention, and later ChatGPT used this algorithm. This technology uses self-attention, multi-head-attention and other mechanisms to ensure the emergence of new content. Moreover, ChatGPT may also generate text by reasoning, and the results can not be summarized by plagiarism.

Embedding constitutes the second feature of ChatGPT, and we can regard the embedding process as enriching some form of content. The development of intelligent technology is divorced from the track of traditional technology development. Traditional technology is often regarded as a single technical article, and its development presents a linear evolution model. However, the development of intelligent technology gradually shows embeddability. For example, as a platform, smart phones can be embedded with many apps. ChatGPT can be embedded in search engines and various applications (such as various word processing software). This kind of embedding can obviously improve the ability of agents. This is the basis of ChatGPT enhancement effect. According to Statista’s statistics, as of January 2023, OpenAI has been closely integrated with science and technology, education, commerce, manufacturing and other industries, and the trend of technology embedding is becoming increasingly obvious. The degree of embedding affects the friendliness of the robot. At present, ChatGPT can’t be embedded in the robot as a sound program. In our contact, it is more like a pen pal. In the future, companion robots and talking robots may be more important, such as voice communication, human talking, machine listening and responding.

ChatGPT’s black box status

For ChatGPT, transparency is a big problem. From a technical point of view, opacity stems from the unexplained problem of technology. Therefore, technical experts attach great importance to the interpretability of ChatGPT, and they also have a headache about the black box effect of neural network. In terms of operation mode, the operation of ChatGPT itself is difficult to explain. Stuart Russell clearly pointed out that we don’t know the working principle and mechanism of ChatGPT. Moreover, he doesn’t think that the large-scale language model brings us closer to real intelligence, and the interpretability of the algorithm constitutes a bottleneck problem. In order to solve this problem, they can observe the mechanism of neural network and touch the underlying logic through some technical methods such as reverse engineering. And through the mechanical interpretable method, the results are displayed in its visual and interactive form. With the help of these methods, they opened the black box of neural network. However, the interpretability obtained by this method is only effective for professional and technical personnel.

From a philosophical point of view, the emergence of black box is related to terminology. Difficult and obscure terms will affect the acquisition of theoretical transparency. For example, the theoretical concepts on which ChatGPT algorithm depends need to be clarified. In the article "Attention is All You Need", attention mechanism is a common method, which includes self-attention and multi-attention If these concepts are not effectively clarified, it will be difficult for outsiders to understand, and the black box will still not be opened. Therefore, one of the most basic problems is to clarify attention itself. However, this task is far from complete. Ethical problems caused by lack of transparency will bring about a crisis of trust. If the principle of ChatGPT is difficult to understand, its output will become a problem. In the end, this defect will affect our trust in technology and even lose confidence in technology.

Enhancement effect of ChatGPT

ChatGPT is an intelligent enhancement technology. What it can do is to intelligently generate all kinds of texts. For example, generate an outline of data ethics and generate the research status of a frontier issue. This obviously enhances the search ability and enables people to obtain higher efficiency in a short time. This enhancement is based on generativeness and embeddedness. From the generative point of view, it realizes the discovery of brand-new objects through the transformation of attention; In terms of embeddedness, it greatly improves the function realization of the original agent.

As an intelligent technology, ChatGPT can obviously improve the work efficiency of human beings. This brings out a basic problem: the relationship between human beings and agents. We divide intelligence into substantive intelligence and relational intelligence. Entity intelligence, that is, the intelligence possessed by entities, such as human intelligence, animal intelligence and entity robot intelligence; Relational intelligence is mainly used to describe the relationship between human beings and agents, and augmented intelligence is the main form of relational intelligence. It is necessary to purify the enhanced intelligence, make it show the general significance of people and technology through philosophical treatment, and make it have normative significance through moral treatment.

However, ChatGPT, which can enhance the effect, will cause some ethical problems. The first is the problem of intelligence gap. At present, this technology is limited, and there is a certain technical threshold, which will lead to the widening gap among users, that is, the gap caused by intelligent technology. This is the gap and gap arising from the acquisition of technology. The second is the issue of social equity. Unless this technology can be as popular as mobile phones, this fairness problem will be exposed very significantly. People who can use ChatGPT to work are likely to improve their efficiency significantly; Those who can’t use this technology will keep their efficiency at the original level. The third is the problem of dependence. Users will feel the convenience of this technology during use. For example, it can quickly generate a curriculum outline, write a literature review, and search for key information. This will make users gradually rely on this technology. But this dependence will have more serious consequences. Taking searching literature as an example, with the help of this technology, we can quickly find relevant literature and write a decent summary text. Although ChatGPT can quickly generate a literature review, it has lost the academic training of related abilities, so the result may be that researchers and students have lost their abilities in this field.

The relationship between ChatGPT and human beings

In the face of the rapid offensive of ChatGPT, academic circles generally take a defensive stance, especially many universities have banned the use of this technology in homework and thesis writing. However, prohibition is not the best way to deal with it. Technology is like water, which can be infiltrated in many ways, so relatively speaking, rational guidance is more appropriate.

To guide rationally, we need to consider the relationship between agents and human beings. I prefer to compare the relationship model between the two to "make the finishing point". Taking the generation of text outline as an example, ChatGPT can generate a data ethics outline based on data processing links around related ethical issues in data processing, such as collection, storage and use. In a narrow sense, this outline is appropriate and can reflect some aspects of ethical issues in data processing. However, from a broad point of view, this outline is too narrow, especially only from the data processing itself to understand data, without considering other aspects, such as dataization, data and lifestyle. What we can do or want to do is to make the finishing touch on the generated text and make it "live" through adjustment. In this way, the position of intelligently generated text has also begun to be clear: it is the finishing touch of human beings that plays a key role in the generation. Without this pen, the intelligently generated text is just a text without soul. If not, it will be difficult to guarantee the meaning and value of human beings, and the corresponding ethical problems will also arise.

Quantum machine learning: the intersection of quantum computing and artificial intelligence

With the continuous progress of technology, the concept of quantum computing is more and more widely known. As a new computing paradigm, quantum computing is very different from traditional computing methods. It can deal with problems that traditional computers can’t handle, which makes quantum computing have broad application prospects in the field of artificial intelligence. Quantum machine learning, as an important field where quantum computing and artificial intelligence intersect, has a wide and far-reaching application prospect. This paper will introduce the basic concept, principle and application of quantum machine learning, and analyze its future development trend.

First, the basic concepts of quantum machine learning

Quantum machine learning is a technology that uses quantum computing to realize machine learning. Its main purpose is to use the advantages of quantum computing to deal with problems that traditional computers can’t handle and improve the efficiency and accuracy of machine learning. The main difference between quantum machine learning and traditional machine learning is that it uses qubits to store and process data instead of classical bits used in traditional machine learning.

Second, the principle of quantum machine learning

The principles of quantum machine learning mainly include quantum data coding, quantum state preparation and quantum algorithm design. Among them, quantum data coding is the process of coding classical data into quantum States, so that the efficiency and accuracy of machine learning can be improved by using the characteristics of superposition and entanglement of quantum States. Preparation of quantum states is a process of putting qubits into the required quantum states. By controlling and operating qubits, the conversion between different quantum states can be realized, thus realizing various algorithms in machine learning. The design of quantum algorithms is the process of designing and implementing quantum algorithms, which can be optimized on quantum computers, thus achieving the purpose of machine learning.

Third, the application of quantum machine learning

Quantum machine learning is widely used, including classification, clustering, regression, dimensionality reduction and other fields. Here are some applications:

  1. Quantum neural network

Quantum neural network is a new type of neural network, which uses quantum bits to store and process data. Quantum neural network can deal with complex nonlinear problems, which makes it have a wide application prospect in image recognition, speech recognition and other fields.

  1. Quantum support vector machine

Quantum support vector machine is a support vector machine algorithm based on quantum computing, which can process high-dimensional and nonlinear data sets faster and improve the accuracy and efficiency of classification. Quantum support vector machine is widely used in bioinformatics, image processing, financial forecasting and other fields.

  1. Quantum clustering

Quantum clustering is a method to realize clustering analysis by quantum computing, which can process a large number of data faster and improve the accuracy of clustering. Quantum clustering is widely used in biology, image processing, market analysis and other fields.

Quantum dimensionality reduction is a method to realize dimensionality reduction analysis by quantum computing, which can process high-dimensional data faster and reduce the complexity and storage space of data. Quantum dimensionality reduction is widely used in data mining, image processing, natural language processing and other fields.

Fourth, the future development trend of quantum machine learning

With the continuous progress of quantum computing technology, the application prospect of quantum machine learning will be more and more extensive. In the future, the development trend of quantum machine learning mainly includes the following aspects:

  1. Further improvement of hardware technology

At present, the performance of quantum computer needs to be improved, and the development of hardware technology will help to improve the efficiency and accuracy of quantum machine learning.

  1. Innovation of algorithm design

With the deepening and development of quantum machine learning theory, algorithm design will become more and more important. In the future, quantum machine learning algorithms will be more complex and efficient.

  1. Expansion of application scenarios

With the continuous expansion of the application scenarios of quantum machine learning, the future will involve more fields, including physics, chemistry, biology, finance, transportation and so on.

To sum up, quantum machine learning, as an important field where quantum computing and artificial intelligence intersect, has a very broad application prospect. In the future, quantum machine learning will continue to develop and innovate in hardware technology, algorithm design and application scenarios, thus bringing more benefits and development opportunities to human society.

AI governance also needs "steering wheel" and "brake pad". How can Shangtang Technology achieve reality-oriented?

Shangtang Technology has implemented the "reality-oriented" concept of digital world development into its own practical development to promote the integrated development of digital economy and real economy.

"Investment Times" reporter Su Hui

In 2023, the two national conferences arrived as scheduled. The reporter of Investment Times noticed that compared with previous years, there was a new change in the two sessions this year, that is, representatives of a number of head Internet technology companies no longer served as NPC deputies or Chinese People’s Political Consultative Conference members due to the expiration of their terms of office, and they successfully completed a new and old transition with the new generation of technology leaders.

For example, He Xiaopeng, chairman of Xpeng Motors, Chen Tianshi, chairman of CAMBRIAN artificial intelligence (AI) chip company, Cao Peng, chairman of technical committee of JD.COM Group, and Kelly Y Zhou, founder and CEO of Zhihu, were all elected as deputies to the National People’s Congress or members of Chinese People’s Political Consultative Conference for the first time. This time, they participated in the two sessions, and they also made active preparations for field research, offering suggestions and suggestions for the development of the industry and a better life.

"Scientific and technological innovation" has always been an important topic to be discussed at the two sessions every year, and the two sessions have always been an important vane for the development of domestic scientific and technological innovation. In this year’s related discussions of the two sessions, the words "cutting-edge technology" such as ChatGPT, humanoid robot and autonomous driving of AI model appeared frequently. A number of representatives in the fields of network security and industrial manufacturing also put forward key suggestions on protecting data security and the development of digital economy.

As a leading artificial intelligence software company in the industry, Shangtang Technology keeps a close eye on digitalization.

In recent years, the digital transformation of agriculture, manufacturing and service industries has been accelerated, which is promoting profound changes in the mode of production of enterprises, lifestyle of residents and social governance. In 2021, the scale of industrial digitalization reached 37.18 trillion yuan, a nominal increase of 17.2% year-on-year, accounting for 81.7% of the digital economy and 32.5% of GDP, and the digital transformation of industry continued to accelerate in depth.

Shangtang Technology relies on AIDC and Shang Tang AI Cloud to create an innovation engine for the digital transformation of traditional industries and deeply stimulate the industrial potential.

AIDC, an artificial intelligence computing center located in Shanghai Lingang, is an AI infrastructure built by Shangtang Technology for digital transformation of the whole industry. AIDC is an important part and physical bearing of computing infrastructure layer in SenseCore Shang Tang AI large-scale device. With multiple leading advantages such as super-large-scale elastic computing power, low computing power cost, high security and low network delay, AIDC builds an innovative base, and drives the upgrading of AI production capacity with higher efficiency and lower cost.

It also opened the technical capabilities of Shang Tang AI big devices to its partners through AIDC, launched SenseCore Shang Tang AI Cloud, a one-stop AI basic service platform, transplanted AI capabilities to the cloud, realized AI as a service AIaaS, provided enterprises with "inclusive, flexible and open" AI infrastructure products and services, promoted the process of AI industrialization and accelerated the digital transformation of the whole industry.

Through Shang Tang AI Cloud, customers can realize the mass production and deployment of high-quality AI algorithms in an efficient, automated and intensive way without deep professional knowledge and huge capital investment, quickly get through the long tail demand in various vertical industries and improve the value chain.

On the other hand, Shangtang Technology always attaches great importance to artificial intelligence governance. The relationship between governance and innovation of artificial intelligence is similar to the relationship between steering wheel, brake pad and throttle of automobile. AI governance is not only like a "steering wheel" that can guide technology research and product development in the right direction, but also has the function of "brake pad", which can stop AI innovation from developing in the wrong direction in time. The strength of the "steering wheel" and "brake pads" needs to be dynamically adjusted according to the priority of the "throttle". Therefore, AI governance needs to adapt to the rhythm changes of technological innovation and achieve a degree of relaxation.

In September, 2022, Shangtang Technology released the White Paper on Artificial Intelligence Governance with Balanced Development —— Annual Report on Ethics and Governance of Artificial Intelligence in Shang Tang (2022). On the basis of AI ethics with Balanced Development, Shangtang Technology further proposed to develop "responsible and assessable" artificial intelligence, and took it as the vision goal of artificial intelligence governance in Shang Tang to create a closed loop of ethical governance.

At the same time, in view of the new stage, new trend and new changes of AI development, Shangtang Technology actively promoted the ethical governance from the exploration of AI itself to the specific business scene field, and in December 2022, it took the lead in publishing the "Reality-oriented Development View of the Digital World-Metauniverse Sustainable Development Report" for the metauniverse scene, introducing Shangtang Technology’s governance proposition for the digital world, providing for the construction of the digital world needed for the development of the real economy.

It can be seen that Shangtang Technology has implemented the "reality-oriented" concept of digital world development into its own practical development, and achieved the goals of "meeting the real needs", "following the real rules" and "conforming to the real interests" through the combination of technological innovation and real industries, so as to promote the integrated development of digital economy and real economy.

Meta develops multi-functional tactile skin Reskin, which can quickly improve machine sensitivity and tactile sensing accuracy.

Nowadays, artificial intelligence gradually integrates with human senses such as sound and vision, making communication between people more convenient. However, it is still challenging to integrate artificial intelligence with human touch.

To solve this problem, Meta AI and Carnegie Mellon University successfully developed a multifunctional, replaceable and durable tactile skin, and named it ReSkin. It can quickly improve the tactile sensing accuracy and sensitivity of the machine in the application process.

(Source:Proceedings of Machine Learning Research )

Related papers are titled "Multifunctional, Replaceable and Lasting Touch Skin" (ReSkin:versatile,replaceable,lasting tactile skins) published in [1].

Matai visiting researcher Raunaq Buhanlan (Raunaq Bhirangi), Tess Hellebrex, postdoctoral fellow and scientist of Pittsburgh Yuan Artificial Intelligence Research Center (Tess Hellebrekers), Mel Majdi, Professor of Robotics Institute of Carnegie Mellon University (Carmel Majidi), Abbina Gupta, Associate Professor of Robotics Institute of Carnegie Mellon University (Abhinav Gupta) is the author of the paper.

It is mentioned in the paper that ReSkin relies on machine learning technology and magnetic sensing technology, and has the advantages of being cheap, multifunctional, durable and replaceable. Specifically, ReSkin has low production cost, only 2-3mm thick, and can interact with the machine model more than 50,000 times. In addition, it has a high spatial-temporal resolution with an accuracy of 90%.Figure | ReSkin is the size of a coin and easy to manufacture (Source:PMLR)

Thin and high-precision specifications make it suitable for all kinds of machines, such as robot hands, tactile gloves, arm sleeves, etc. For specific processes, ReSkin can also provide tactile signals (high frequency) for the sliding, throwing, catching and clapping operations of the machine.

When Reskin is applied to different products, a large amount of relevant data will be generated, which can help researchers improve their tactile perception ability in AI systems.

Figure | Frequency changes of sensors applying ReSkin under different magnetic fields (Source:Proceedings of Machine Learning Research)

For example, ReSkin is an elastic sheet that can change its shape and contains magnetic particles. When its shape changes, it will release different magnetic signals. Researchers can use magnetometer to measure these changes, and use data-driven technology to convert the measured data into information such as contact position and applied force.

At present, many tactile sensing experiments are limited to one sensor level. This is because every time ReSkin is replaced, the machine needs to build a new model, which reduces the transmission efficiency.

Moreover, in different scenarios, each sensor needs to be thoroughly calibrated with the initial calibration procedure to match its individual response. This means that the calibration procedure must also adapt to these changes. In addition, as time goes by, soft skin like ReSkin will deform and need to be replaced, so it is difficult to popularize and apply it to different interactive scenarios.

In order to simplify the replacement process of Reskin, the researchers made innovations in three aspects.

Firstly, the researcher separates the internal circuit of the sensor from the passive interface, and does not need to be electrically connected with the traditional measuring electronic equipment. This operation effectively improves the sensitivity of the sensor, and it is as simple as sticking a sticker when replacing worn ReSkin.

Secondly, the researchers use the output data of several sensors to improve the model mapping. Through this operation, researchers can use a higher data diversity training model. This helps the sensor to output more effective and generalized data.

Thirdly, thanks to the self-supervised learning mode of the machine, researchers don’t have to collect calibration data for each new sensor, but use a small amount of unlabeled data to automatically fine-tune the sensor.

It is known that the existing camera-based tactile sensor requires a very small contact distance between the surface and the camera, which leads to a heavier machine. In contrast, ReSkin can cover the hands and arms of humans and robots, which facilitates researchers to develop multifunctional, expandable and inexpensive tactile modules. This is impossible for the existing artificial intelligence tactile system.

In order to highlight the practical value of ReSkin and show its unique charm of promoting the development of artificial intelligence, researchers apply it to different machine scenes. From grasping tiny objects to measuring the force exerted by the dog’s feet, from building a continuous ReSkin with wide coverage to measuring the field contact force, ReSkin has shown its extremely high flexibility and practicality.

Although researchers have demonstrated the technical advantages of ReSkin in contact location and force prediction, ReSkin still has great development potential in the future.

The experiment of this paper is based on the single-point contact of the machine, and the goal of scientists is to further study the application of ReSkin under multi-point contact. Another interesting future development direction is to specifically analyze the influence of external magnetic field and metal objects on ReSkin’s perception ability.

In addition, based on ReSkin’s high time resolution of 400Hz, researchers can make use of this advantage and use dynamic time series data to create better machine models. In a word, scientists believe that ReSkin will promote the machine’s touch perception ability and be able to apply it to practice.

References:
1.https://arxiv.org/abs/2111.00071
2.https://ai.facebook.com/blog/reskin-a-versatile-replaceable-low-cost-skin-for-ai-research-on-tactile-perception/

President china portrait photography society and his party visited Meitu Company for a discussion.

Recently, Mr. Yan Taichang, Chairman of china portrait photography society, Mr. Han Yuezhi, Vice Chairman of china portrait photography society and Chairman of Post-production Professional Committee, Mr. Liang Jiande, Vice Chairman of china portrait photography society and Chairman of Cosmetic Modeling Professional Committee, and their delegation visited Meitu Company for exchange and discussion. Also present at the visit and discussion were Xu Chunsheng, Chairman of Platinum Jue Travel Photography Culture Group Co., Ltd., and Pan Baofu, founder of Extraordinary 6+1 Photography Group. Zheng Minglie, Chairman of Wiener Digital Printing Art Industrial Park, He Songlin, Senior Vice President of Meitu Company, Chen Jianyi, Vice President of Products and Xu Qingquan, Head of Meitu Yunxiu, accompanied him to visit and attend the symposium.

In the exhibition hall of Meitu Company, Chairman Yan Taichang and his party learned about the development history, company strategy, corporate culture, product innovation, core technologies and honors of Meitu Company in detail, and experienced the software and hardware products of Meitu, such as Xiu Xiu, Beauty Camera, Wink, Meitu Skin, etc. On the spot, they paid attention to and recognized the innovative products and leading imaging technologies of Meitu Company. During the introduction of Meitu’s corporate strategy, Chairman Yan Taichang and his party learned deeply that at present, Meitu, based on its image core competence, digs more scenes at the C-end, while focusing on the B-end market with SaaS and related businesses as its main focus. Based on Meitu’s continuous investment in scientific and technological innovation, accumulated grasp of the public’s aesthetics over the years, and understanding of the needs of a large number of users, Meitu Yunxiu, a one-stop intelligent retouching solution for the commercial photography industry, is launched. In this regard, Mr. Yan Taichang said that the imaging technology mastered by Meitu can solve the technical problems existing in the portrait photography industry in a targeted manner, and help photographers, retouchers and enterprises to improve retouching efficiency with the help of artificial intelligence technology, and help the standardization construction and digital transformation of the industry.

At the symposium, the two sides had an in-depth sharing and exchange on the current situation, pain points and future development direction of portrait photography industry. With the consumption upgrade of portrait photography industry, all enterprises are facing new opportunities and challenges. Both sides said that since the formal strategic cooperation was reached, through multi-field and high-level in-depth cooperation, more and more photographers and enterprises actively embraced the digitalization of portrait photography, and jointly explored and developed the digital economy with Meitu Yunxiu. "Technology" and "digitalization" are the key words for the development of portrait photography industry. Focusing on china portrait photography society’s leading role in the industry, Meitu Yunxiu will give full play to its technical advantages in the field of imaging technology, actively promote the continuous deepening of cooperation between the two sides, focus on overcoming the shortcomings of the industry, rely on image AI technology, jointly promote the high-quality development of portrait photography industry, and serve high-quality post-retouching to help portrait photography. Help the upstream and downstream industries to realize all-round digital transformation and upgrading. The head photography brands and later brands who participated in this symposium all said that intelligent retouching technology can actually help enterprises reduce costs and improve efficiency, and imaging technology is playing an increasingly important role in portrait photography ecology. Therefore, we should work together to seize the opportunities of digital development, promote the development of new businesses in various fields of the industry, create new formats, explore new modes, and make greater contributions to the digital transformation of portrait photography.

The person in charge of Meitu Yunxiu said that as one of the important strategies of Meitu’s B-end layout, Meitu Yunxiu is committed to promoting the high-quality development of portrait photography industry and serving high-quality post-retouching. Relying on the continuous breakthrough and innovation of imaging technology, Meitu Yunxiu will launch the first multi-terminal adaptation mode in the industry, flexibly adapt to complex equipment and network environment, and provide better and more convenient intelligent retouching services for enterprises and retouchers, helping enterprises achieve cost reduction and efficiency increase.

Since the two sides reached a strategic cooperation in 2022, based on the multi-dimensional cooperation between online and offline, the two sides have achieved a lot. As a strategic partner of china portrait photography society, Meitu Yunxiu will give full play to its advantages in imaging technology and artificial intelligence, further deepen cooperation with china portrait photography society, promote the digital and intelligent development of portrait photography industry, and comprehensively help accelerate the development of digital economy of portrait photography industry in China.