人工智能区块链演讲稿范文,人工智能区块链演讲题目

人工智能（AI）是指计算机程序实现的智能，它可以模拟人脑的思维过程，以解决复杂的问题。目前，AI已经被广泛应用于各行各业，从金融到医疗，从机器人到自动驾驶，都在不断推动着人类的发展。而基于区块链技术的人工智能（AIBC）正在成为一种新兴的技术，它将AI与区块链技术相结合，以提供更安全、更可靠的服务。

区块链技术是一种分布式账本技术，它通过分散的节点来存储和传输数据，从而构建一种去中心化的网络，从而提供更安全、可靠的服务。区块链技术的核心特点是去中心化、安全性和透明性，它可以抵御攻击，保护数据的安全性，并可以提供更可靠的服务。目前，区块链技术正在被广泛应用于各行各业，从金融到物联网，从政府到娱乐，都在不断推动着人类的发展。

人工智能区块链（AIBC）是将AI与区块链技术相结合的一种新兴技术，它可以提供更安全、可靠的服务，并可以实现更高效的数据处理和智能分析。AIBC通过使用区块链技术，可以抵御攻击，保护数据的安全性，同时可以提供更可靠的服务。此外，AIBC还可以支持大数据分析，从而更好地分析和预测用户行为，提高用户体验。

未来发展人工智能区块链技术正在成为一种新兴的技术，它将AI与区块链技术相结合，以提供更安全、更可靠的服务。未来，人工智能区块链技术将会在各行各业中得到更广泛的应用，从金融到物联网，从政府到娱乐，都将会从中受益。同时，AIBC也将会推动着智能分析和大数据分析的发展，从而帮助企业更好地分析和预测用户行为，提高用户体验。

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Ⅰ At the 2022 World Artificial Intelligence Conference, which blockchain company representatives spoke?

At the 2022 World Artificial Intelligence Conference "Web3.0 Digital Economy Development Summit Forum" , Dr. Li Wei, founder and CEO of Qulian Technology, a blockchain unicorn company, gave a keynote speech titled "Blockchain: The Core Infrastructure of Web3.0", explaining in depth why the district Blockchain is the core infrastructure of Web3.0.
Dr. Li Wei said that blockchain provides an effective trust mechanism and value transfer method for the Internet, making data credible, assets credible, and cooperation credible. Web3.0 with blockchain is the Internet of value.

Ⅱ Five major tracks, eight experts, the AI ​​world in the eyes of people in the banking industry

Who said elephants can't dance?

For all banks, 2020 will be an ultimate test without warning, the most intuitive financial technology showdown. The epidemic has caused branch traffic to plummet to close to zero, challenging banks' online service levels in all aspects, and testing how much of the increasing investment in technology over the years has truly turned into digitalization and intelligence.

Entering 2021, banks are ushering in the best time to conduct a thorough review and prepare for the move.

In the past year, banks have worked harder to get rid of the stereotype of the elephant turning around, saying goodbye to the past dilemma of being pushed forward by various innovations, and trying to take on more responsibilities in the wave of financial technology and new digital infrastructure. A proactive and open-minded person who keeps moving forward with a brisk and agile pace.

No bank does not want to embrace AI, and no one wants to miss the future of digital transformation. In the process of sorting out the overall AI layout of dozens of banks and sharing with many guests at the "Banking AI Ecosystem Cloud Summit", we gradually discovered that the challenges and dilemmas of banking AI are also opportunities.

Data security and privacy protection

AI in the banking industry is first blocked by the data dilemma faced by AI itself and the increasingly tightened data regulatory standards.

While the technological dimension continues to advance, an issue that banks must consider is: How to balance business innovation and privacy protection?

The "Federated Learning Series Open Course" hosted by Leifeng.com AI Financial Review has conducted a systematic and in-depth discussion on this issue. In the first class, Yang Qiang, Chief Artificial Intelligence Officer of WeBank, pointed out directly: "The power of artificial intelligence comes from big data, but in the actual application process, most of the data encountered are small data."

Wang Jianzong, deputy chief engineer of Ping An Technology, also pointed out in the class, “Traditional AI technology must learn from massive amounts of data or mine some relevant features, use mathematical theory to fit a mathematical model, and find input and output. Correspondence, such as the weights and biases of the training network in deep learning, model effects and dataMagnitude, quality, and data authenticity are closely related. "

A typical example is bank credit risk control: most AI applications are now driven by data, and credit risk control requires a lot of data training, but there are very few cases of large-amount loan risk control. "If To build a deep learning model, it is far from enough to use only a small number of samples of such large loans. "Yang Qiang explained.

Small data needs to be "gathered into towers", and at the same time faces the possibility of privacy infringement. For this reason, legislation in the field of network security and data compliance has entered the fast lane, and data abuse and crawlers have also been subject to Overly severe rectification.

Although the "Data Security Law" is still in a draft state, the draft clearly states that attention should be paid to the use of data itself, and it is necessary to promote data protection on the premise of protecting citizen organizations and related rights and interests. Economic development as a key factor.

Data is called the oil field of the new era, but how can banks use AI to find more efficient and compliant mining tools?

In In the first speech of the "Banking Industry AI Ecological Cloud Summit", Dr. Yan Qiang, a blockchain security scientist from WeBank, conducted an in-depth discussion on the necessary data security and privacy protection thinking for banks. He pointed out:

In the era of digital economy, the development of AI in the banking industry must respect "data islands" as the original ecology of the data industry, and privacy protection technology is the key to breaking the "zero-sum game" of data value integration. , it is necessary to open up the "double cycle" of collaborative production of private data.

Blockchain is the best technology to carry data trust and value. Common problems such as data quality in privacy computing and AI applications can be complemented or improved through blockchain.

Multiple AI technology routes such as federated learning, TEE trusted computing, and secure multi-party computing are also trying to be implemented in the core business scenarios of banks.

AI Financial Review learned that in addition to WeBank, Bank of Jiangsu has also explored the direction of federated learning in 2020. They have cooperated with Tencent’s security team to jointly develop intelligent credit card operations based on federated learning technology. and plan deployment, and conduct financial risk control model training with the support of federated learning technology.

Bank database

Taking "data" as the line, the upgrade track of the bank's front, middle and back offices is clearly visible.

If we talk about banking technology in the past few years, the discussion was more focused on front-end intelligent applications, then now the middle and back-end construction has begun to come more into the spotlight, discussing the value and value they present for the digital transformation of banks. significance.

An important module in this is the transformation and upgrading of the bank database.

We once reported that since Oracle entered the Chinese market, it has had an overwhelming advantage in the bank database market and has been the first choice for many banks.

ByDue to long-term use of Oracle, many banks have developed serious path dependence. Li Zhongyuan, head of distributed database technology at Ping An Bank, also told AI Financial Review that system migration and re-construction require a lot of costs. From a single machine to a multi-machine group, the probability of failure and maintenance costs will increase, which will increase the cost of system migration and reconstruction. Overall system operation and maintenance will be a huge challenge. (For details, see "The Day the Banking Industry "Seeks Change", When Domestic Databases "Break")

However, as the needs for banking business innovation become more and more complex, traditional databases are facing difficulties in terms of technology boundaries, costs, and controllability. There is an increasing mismatch in terms of gender; the single source of procurement database also puts banks in a very passive situation.

The emergence of cloud computing has shaken Oracle's near-monopoly position in the database market, and major Internet cloud vendors have entered the battlefield.

Li Gang, vice president of Tencent Cloud, said that the cloud database is characterized by low cost and easy expansion. It can be run on any X86 PC server and theoretically has unlimited horizontal expansion capabilities. These are advantages that traditional databases such as Oracle cannot match.

As a result, thousands of banks in China gained more choices and began to migrate from centralized databases to distributed databases. A long journey related to the "downward migration of big machines" began.

There are already pioneers in this change. For example, Zhangjiagang Bank placed its core business system on Tencent Cloud TDSQL database in 2019. For the first time, a traditional bank chose a domestic distributed database for its core system; in 2020, The core system of Ping An Bank's credit card has also been switched and put into production. The new core system also uses a domestic database.

At the "Banking Industry AI Ecological Cloud Summit", Zhang Wen, chief architect of Tencent Cloud Database TDSQL, shared in depth two typical database migration and transformation cases of Zhangjiagang Bank and Ping An Bank.

Take Ping An Bank as an example. Its large size means that application transformation is more challenging. Zhang Wen explained that in order to cooperate with this transformation, the application introduced a microservice architecture to split and decouple the application. The distribution of accounts is divided into units, with DSU as a logical unit. A single DSU contains 2 million customer information, and a single DSU handles both online and accounting services.

However, domestic distributed databases are also still growing. Zhang Wen also pointed out that financial-level distributed databases currently face a series of challenges. In addition to having scalable and expandable capabilities, they must also solve high-level problems. Availability, strong data consistency, while exploring more cost-effective performance costs, and creating easier-to-use, more product-oriented mature solutions for financial institutions.

China-Taiwan Construction

The popular keyword "China-Taiwan Construction" is no longer exclusive to Internet companies. Banks are no exception and even need a middle office.

Large institutions such as banks, the structure is extremely complex, and there is cross-department and multi-team collaboration. The accumulation of massive data over time is like a dilapidated building that has been in disrepair, requiring timely and continuous management.

It seems that banks have a large amount of data, technology and talents, but the resources are often "used in their own way". There is no sense of cooperation between departments and they build independent chimneys; the technology is superficial and cannot be linked or deepened. This resulted in a huge waste of bank resources.

Only through the systematic construction and smooth operation of the middle platform can the "dead knots" in this huge system be untangled one by one.

Wang Yongqing, Chairman of the Board of Supervisors of China Construction Bank, once pointed out: The construction of middle platform is a key link in the digital transformation of commercial banks. He believes that the inevitable destination of digital transformation of commercial banks is ecological and scenario-based.

Although commercial banks have accumulated certain competitive advantages over many years of operation and formed internal ecosystems with their own characteristics, they are still closed and aloof at present and cannot meet the needs of the open digital economy. Ecological management requires interaction, high stickiness, sense of touch, and no boundaries.

Therefore, China Construction Bank has also taken the lead in the data center, which can be summarized as 5U (U means unified), including unified model management, unified data services, unified data views, unified data specifications and unified data management.

In order to easily support hundreds of millions of users and achieve high-efficiency, high-concurrency scenario-based operations, China Merchants Bank has also continued to make efforts in the construction of the middle platform and technology ecosystem in the past two years. The China Merchants Bank App 9.0 released at the end of last year has more than 1,800 iterative demand points, and the construction of "10+N" digital middle office accounts for a considerable proportion.

How to build the data center that financial institutions need?

At the "Banking Industry AI Ecological Cloud Summit", Zhang Jiaxing, chief scientist of 360 Digital, used "three links and three fasts" to summarize the standards of the data center:

For financial institutions Facing a large number of users and complex businesses, an excellent data middle platform must achieve multi-business integration, internal and external data interoperability, and user relationship connectivity. At the same time, it must achieve fast real-time data processing, fast usage, and fast demand response.

He further emphasized that data and AI are very closely integrated. If the data middle platform and the AI ​​middle platform are built separately, there will inevitably be a separation between the two.

Based on this, 360 Digits also launched its own data AI fusion middle platform, which integrates the top-level data platform, to the platform services supported by intermediate data services, and then to the management of the entire data assets, to the bottom The design of the entire data technology architecture has been adjusted and its accumulated AI capabilities have been embedded into it.

Zhang Jiaxing also revealed in his speech at the Cloud Summit that 360 Digits has developed a federated learning technology-segmented neural network. Through the neural network in high-dimensional space, the irreversible characteristics of Embedding allow different participants to participate.The data partners only need to pass the Embedding vector and cannot see the original data, but they can ultimately make the model produce the target effect.

Intelligent risk control of bank credit

In the past year, bank credit risk management has remained one of the most concerning directions.

On the one hand, the attention comes from the sharp increase in loan overdue and bad debt risks due to the impact of the epidemic. How to use technical means to "stabilize this bowl of water", grasp the scale of credit support, and become a bank and consumer finance company. A big test for companies and risk control technology service providers at the beginning of the new year. (For details, see "The Credit War "Epidemic": A New Year's Test for Risk Control")

On the other hand, starting from the second half of 2020, the "red line" for the supervision of financial technology or Internet finance will be "It gradually became clear. For example, the "Interim Measures for the Administration of Internet Loans of Commercial Banks" clearly set out the risk management and control requirements for commercial banks and the management regulations for cooperative institutions.

Although intelligent risk control combined with AI and big data is no longer new in banking technology applications, this does not mean that intelligent risk control is mature enough - data resource barriers, own data accumulation, data Feature extraction and algorithm model improvement are considered to be the four major dilemmas currently faced by big data risk control.

The person in charge of a commercial bank once said that there are common data quality problems in the process of model construction and model application, including the falsification of external data (black product fraud) and the abuse of internal data. During model iteration, On the other hand, many banks only pursue the speed and frequency of iterations, but ignore the final effect.

Wang Jin, former Internet financial CRO and CEO of Ronghui Jinke, further pointed out that factors such as incomplete data standardization and governance systems, poor data quality and high missing rate, insufficient technical capabilities, and lack of comprehensive scientific and technological talents are all factors. This is an important reason why banks and other financial institutions cannot make good models.

Wang Jin once worked at American Express, known as the "Risk Control Whampoa Military Academy" for 17 years, and was responsible for providing policy systems and independent monitoring for more than 700 models related to various products in various countries around the world. At the Cloud Summit, he also analyzed the conceptual misunderstandings in financial risk management based on his more than 20 years of risk control experience.

"Many people do not particularly understand that risk management is always a science of finding a balance point." Wang Jin believes that risk management balance has three core questions:

He also Analyzed the core elements of risk management balance for banks and other licensed financial institutions. When it comes to risk management, the most important thing is the control of data. “Financial companies must think about the life cycle of data when they are established. First of all, they must start with the business When selecting products and customers, decide what kind of data is needed."

Data strategy is a relatively long-term implementation process. Organizations must first establish the principles and conditions for data selection: they must consider more than just data compliance, stability and coverage, but also the freshness and timeliness of the data.effectiveness and time span.

From the perspective of model construction, Wang Jin pointed out that an excellent risk control model should have five major elements: discrimination, accuracy, stability, complexity and interpretability. "raw materials" data, model The choice of architecture and algorithm, the emergence of derived variables, the monitoring and iteration of the model, as well as the definition of y and the screening of samples all affect the "forging" of the model.

In his view, it would be ideal for banks and other financial institutions to be efficient and complete in terms of identity identification and control, data security management, risk model management, and automated monitoring systems. a state.

RPA and internal process optimization

There is another keyword that appears more and more frequently in the annual reports of various banks, and that is RPA (robotic process automation). Previously, AI Financial Review also held the "RPA+AI Series Open Class", inviting five top RPA vendor executives to share the sparks of the collision between RPA and finance.

The definition of RPA can easily be associated with the “process banking” transformation wave around 2012. Process banking at that time meant transforming the traditional banking model by restructuring the bank's business processes, organizational processes, management processes and cultural concepts to form a new bank operation and management system with process as the core.

Today, banks’ transformation battle has been upgraded to “digital transformation” in all aspects. The optimization and transformation of internal processes continues to advance with the support of AI and robotics technology. RPA has quickly become an indispensable part of banks’ digital transformation. Put the "weapon".

Ji Chuanjun, co-founder of Daguan Data, pointed out at the "Banking Industry AI Ecological Cloud Summit" that the most obvious value that RPA+AI brings to banks is to reduce manual work, reduce manual errors, and improve business process efficiency, while also improving risk warning and monitoring capabilities.

AI Financial Review noted that many state-owned banks have put RPA into actual business.

Take ICBC as an example. The application of RPA in ICBC covers multiple business scenarios such as front-office operations, middle-office circulation and back-office support. It is the first in the industry to launch and promote an enterprise-level Robotic Process Automation (RPA) platform. Application, a total of 46 head offices and branches across the bank have implemented 120 scenarios using RPA.

China Construction Bank has also introduced RPA, establishing the first domestic enterprise-level RPA management and operation platform, agilely developing 100 business application scenarios, and realizing automation of manual links and machine control of risk links.

The Agricultural Bank of China revealed that the Agricultural Bank of China is still in the technology platform construction stage, and will later use credit card business, financial business, etc. as pilot projects to implement RPA needs. Its implementation strategy is to build a unified RPA technology platform for the entire bank and export RPA services to all departments of the head office and branches.

Bank of China in 2By the end of 2017, its subsidiary company BOC International had proof of concept of RPA. The team successfully put into production 20 robots, each performing more than 30 automated processing tasks involving different business processes in different positions. It also cooperated with RPA vendor Daguan Data.

Ji Chuanjun also shared the current implementation of AI+RPA in various typical scenarios in banks at the Cloud Summit:

For example, smart credit is oriented to the core process of the entire bank— —The credit process is divided into three stages: pre-loan, loan, and post-loan. It involves professional links such as data query, data processing, financial statements, and bank flow. It is necessary to complete the entry of basic information and the review of due diligence reports. A large amount of repetitive work in these links can be completed automatically based on technologies such as AI, OCR, and NLP. .

Ⅲ Talking about technological changes - the evolution of artificial intelligence, Internet of Things, and blockchain

I have read a lot of reports about blockchain recently and feel that blockchain is very popular. It has many similarities with the popularity of artificial intelligence and the Internet of Things. The following are some personal opinions:

1. The emergence of artificial intelligence, the Internet of Things, and blockchain are all human exploration of the future.

Human beings are a very peculiar group. There is always a group of people who will find an exit in our era, so that we can feel that society is functioning normally. Because of the explosion of technology, people's desire for innovation is unprecedented. Regardless of the outcome, the starting point of these desires is always good.

On the one hand, the popularity of artificial intelligence is due to the development of these three aspects, which we often call deep learning, big data, and computing power; on the other hand, the Internet has been developing for decades and requires new technologies. Things emerge to take over the consequences of the development of the Internet, such as big data and some inefficient Internet mechanisms. The Internet has been developing for so many years, and during this period we can also see some new things being invented or mentioned, such as the Internet of Things. However, it gradually faded over time. At the beginning, when the Internet of Things appeared, many people thought that the Internet of Things was the next exit for mankind after the Internet. Later, many problems emerged, such as limitations in data processing capabilities and limitations in sensor intelligence, and the Internet of Things was gradually marginalized. Then came the emergence of solutions to problems in the development of the Internet of Things - artificial intelligence.

On the whole, the development of these technologies has either been truly successful, or it has led to some new problems, and the solutions to these new problems have formed new technologies. This reminds me of what Mr. Wang Qiang of ZhenFund said: It is the questions, not the answers, that change the world.

After so many years of development of human society, there is always a problem that needs to be solved, and that is decentralization. It is worth explaining that the blockchain is not completely decentralized, but only an improvement in efficiency, which also has costs. todayMany media reports are themselves misleading.

2. Who is the next exit between blockchain and the Internet of Things?

The author believes that the Internet of Things is the next exit for mankind. Compared with blockchain, the Internet of Things is more likely to become a new outlet, because the previous wave gave it certain advantages in policy, and compared with the Internet, the Internet of Things is a decentralized network. Here is an explanation of what a decentralized network is. The Internet is a platform-centric network. Communication between people must be concentrated on a platform. This platform is what we often call a trust mechanism. The Internet of Things is a decentralized network. Sensor devices self-organize into a network. This network node is no longer an enterprise or a platform. In other words, the platform distributes and optimizes centralized rights, making each node possible to become the center.

As for the blockchain, the decentralization that its core technology demands is still too urgent. However, in some fields, this kind of decentralization demand is still welcome, such as finance, house leasing and other business needs that are suitable for the p2p model. The author believes that the biggest reason why the next exit is the Internet of Things is that compared to the blockchain, the decentralization of the Internet of Things is softer.

3. Artificial intelligence, the Internet of Things, and blockchain will eventually be applied to life.

This sentence may sound a bit nonsense. However, the premise that technology can be applied to life is that the technology itself can solve a series of problems that exist in life. From an economic point of view, all technologies revolve around two words: efficiency. No matter how people view artificial intelligence, the Internet of Things, and blockchain today, one thing is certain: existence is value.

As for the time dimension, we can feel or see that after more than a year of hype, artificial intelligence is gradually being implemented in the industry. Personally, 2018 should be the first year for artificial intelligence to embrace the industry. On the one hand, technology companies and traditional companies are also actively cooperating. On the other hand, new media related to artificial intelligence are also promoting the implementation of artificial intelligence, such as: New Wisdom.

Needless to say about the Internet of Things, the previous government also favored the Internet of Things in policy formulation and related planning. Moreover, in the past few years, commercial applications of the Internet of Things have been developing well. But, it's not as good as I thought before. I believe that with the cooperation of artificial intelligence, the Internet of Things industry will develop rapidly in the future.

For blockchain, it may take a long time to eliminate the bubble. Today’s blockchain bubble is too serious. In addition to market bubbles, blockchain also has to face very severe challenges. Supervision, these issues will take a long time to resolve. Personally, I think it will take longer for blockchain to be introduced into the industry than artificial intelligence.time. As for many companies today, it is better to concentrate on doing things than to join in the fun. When supervision is unclear, problems are prone to arise in joining the heat.

IV Cai Esheng: The core of financial technology is still artificial intelligence and blockchain

Financial website news In 2020, the sudden epidemic broke people’s normal life, and the world The economy has undergone turbulent changes and uncertainty has increased significantly. China's financial industry has encountered huge challenges. In the same year, bank wealth management subsidiaries were born, financial technology empowerment is in full swing, wealth management transformation is surging, and the fund industry is facing unprecedented changes. tuyere. On December 10, the 5th Smart Finance International Forum and the 2020 Financial Industry Leadership Annual Ceremony hosted by the financial industry were held in Beijing. Hundreds of financial industry figures gathered together to discuss the digital transformation and development of the financial industry and the role of financial technology in wealth management. We conducted in-depth and pragmatic discussions and exchanges on topics such as application in the field, the era of public funds, and the future of pension finance.

Mr. Cai Esheng, former Vice Chairman of the China Banking Regulatory Commission, attended the forum and delivered a speech on the theme of "Financial Intelligence and Financial Technology Development Trends". Cai Esheng said that the development of financial technology and financial intelligence are a very hot topic. In the past two years, the development of financial technology has shown leaps and bounds, but it has also encountered some problems. He pointed out that whether it is financial development, smart finance or financial technology, they are actually designed to serve the development of the real economy.

Regarding the development of the financial industry, Cai Esheng expressed his four views:

First, innovation is a core position in future development and is also a new development concept. Article 1. One direction of the financial support innovation system is to promote the industrialization and scale of new technological achievements. The concept of financial development should be clarified. This is the next step for the financial industry and financial system to solve.

Second, it is necessary to build a mechanism and system for finance to effectively support the real economy, improve the level of science and technology, and enhance financial inclusion. Finance should be a leading industry that uses science and technology to improve service capabilities. As for financial technology itself, we must actively use technological means and intelligence to develop around improving efficiency and quality.

Third, the core of financial technology is artificial intelligence and blockchain. The 14th Five-Year Plan proposes to promote the deep integration of various industries such as the Internet, big data, and artificial intelligence, promote "digital industrialization" and "industrial digitization", and promote the integration of the digital economy and the real economy. Then, the intelligence of the financial industry must be synchronized with the development of the digital economy of the entire society and the digital demand of all walks of life, or even higher than it. How to solve the problem of multi-level services under the contradiction of imbalance and insufficiency needs to be taken into consideration.

Fourth, financial development must not only improve service levels, but also solve security problems and prevent risks. The future of Internet financedevelopment, there are five points that need to be considered: network security, civil competition and antitrust, new types of too-big-to-fail, ownership of data rights and issues of international coordination of cross-border data flows.

IV ICBC Vice President Zhang Wenwu: Creating a future-oriented smart financial ecosystem

On November 11, ICBC Vice President Zhang Wenwu attended the "15th 21st Century Asian Financial Annual Conference" and delivered a keynote speech entitled "Smart Technology Open Finance to Create a Future-oriented Smart Financial Ecosystem".

Zhang Wenwu said that currently, financial technology has become an important force in improving my country’s independent technological innovation capabilities, external radiation capabilities, risk prevention and control capabilities, and building a “Digital China”. At the same time, the policy environment, customer demands, and financial supervision faced by banks are also undergoing profound changes, providing new opportunities for the banking industry to use financial technology to carry out financial innovation and promote the opening up of financial services.

He believes that new opportunities breed new changes. Focusing on the growing customer needs, commercial banks build collaborative smart finance internally, expand open and shared smart ecology externally, and promote bank financial services towards "online + offline", "industry + outside the industry" and "artificial + intelligence" direction of evolution. Facing the future, the banking industry must follow the trend, focus on the two priorities of openness and innovation, deepen the financial scene, improve service efficiency, and create a smart ecosystem.

The first is to deepen data governance and make finance more penetrating. As a new factor of production, data will further stimulate the total factor productivity of the banking industry. Banks must seize the opportunity of data element market reform, strengthen data sharing and technical cooperation, release the potential of data assets, and make data assets more practical, viable, and stronger. Focusing on the construction of basic capabilities driven by the two wheels of data and technology, ICBC has independently built an industry-leading big data cloud platform and created a group data element market. By building a distributed integrated data intelligence platform, it has injected "breadth and expertise" into financial development. New vitality of data services with depth, speed and accuracy.

The second is to build an open ecosystem to make finance more accessible. Adhering to the development concept of openness, cooperation and win-win, banking financial services should combine "going out" and "bringing in". On the basis of a clear understanding of partners, we should cooperate with all walks of life in society to build scenarios and proactively deploy Open financial ecosystem. ICBC exports thousands of standardized products and services to thousands of partners through its API open platform, leading the industry in API openness capabilities and number of partners; through the financial ecological cloud, it introduces applications in many industries such as finance, education, and scenic spots, etc. Working with partners to provide customers with comprehensive "industry + financial" services, the number of ecological cloud tenants has reached 30,000, initially building a rich and diversified ICBC cloud ecosystem.

The third is to deploy intelligent technology to make finance more intelligent. Intelligent technology layout is a process of continuous improvement in level and continuous improvement of functions. It will follow the financial market.The market environment changes, user needs upgrade, new technologies and new products continue to iterate and innovate and upgrade. The banking industry must continue to increase technological innovation, continuously improve the core competitiveness of financial technology, and stimulate new vitality for business development. ICBC has built a series of independent and controllable new technology platforms such as artificial intelligence, blockchain, Internet of Things, and 5G, and leads the banking industry with more than 700 patent authorizations.

The fourth is to innovate smart services to make finance more inclusive. As an important way to practice digital inclusive finance, fintech is solving the problems faced by the development of inclusive finance such as high costs, insufficient returns, and difficulty in achieving both efficiency and security, and improving the coverage, availability, and inclusiveness of financial services. . In recent years, in accordance with the decisions and arrangements of the Party Central Committee and the State Council, ICBC has used financial technology to continuously improve its financial service capabilities in key areas such as small and micro enterprises, public benefit, private enterprises, and poverty alleviation. For example, we build online platforms such as mobile banking and account manager cloud studios, innovate new financial products such as e-loans and digital credit cards, and build three inclusive products: "operating quick loans", "e-offset quick loans" and "e-chain quick loans" Financial product system, launched the "Global Matching Club" cross-border matching platform, and initially built a new system of smart financial services that is more open, inclusive and shared.

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VI Create with the same core, build the future intelligently丨From concept to implementation, the Industrial Internet of Things helps upgrade "intelligent manufacturing"

< p> On June 29, the "2019 Future Forum Nanjing Summit" co-sponsored by the Nanjing Municipal People's Government and the Future Forum, and hosted by the Nanjing Branch of the China Council for the Promotion of International Trade, the Nanjing Economic and Technological Development Zone Management Committee, and the Nanjing International Chamber of Commerce, officially At the opening, the theme of this summit is "Co-creation and Collaboration".

At the opening ceremony, Hu Hong, deputy mayor of the Nanjing Municipal People's Government, and Zhou Kui, partner of Sequoia Capital China and director of the Future Forum, as representatives of the organizers, expressed their welcome and gratitude to all the guests. . Shen Yinlong, deputy director of the Nanjing Economic and Technological Development Zone Management Committee, focused on the creation of the "China (Nanjing) Smart Valley", a new landmark in the artificial intelligence industry.

In the subsequent keynote speech session of the conference, Qiushi Distinguished Professor of Zhejiang University, dual-employed professor of the First Affiliated Hospital of Zhejiang University School of Medicine, Director of the Institute of Applied Mathematics of Zhejiang University, Image Processing Research and Development Department of the School of Science of Zhejiang University Kong Dexing, director of the center and director of the Hangzhou Innovation Center of the National Engineering Laboratory for Big Data Algorithm and Analysis Technology, Chen Datong, chairman of the Yuanhehua Venture Capital Committee and director of the Future Forum, professor at Imperial College London and chairman of the Professional Committee of the China Artificial Intelligence Industry Innovation Alliance And Lu Yongqing, co-founder and chief scientist of Kunyun Technology, fellow of the British Computer Society (BCS), academician of the Royal Academy of Engineering, and fellow of the Institute of Electrical and Electronics Engineers (IEEE), Yu Kai, founder and CEO of Horizon and youth director of the Future Forum, Bringing domesticThe most cutting-edge scientific research information and results transformation experience.

At the morning forum, outstanding entrepreneurs, scientists and investors in the industry gave speeches and innovative dialogues around the two hot technology fields of Industrial Internet of Things and Chinese Chips.

Intelligent manufacturing is an important breakthrough for revitalizing the real economy and accelerating industrial transformation and upgrading. In recent years, our country has successively launched a series of strategic plans for intelligent manufacturing. Digitalization and networking through the industrial Internet of Things can improve the production efficiency and product added value of enterprises and alleviate production costs.

In his keynote speech on "Industrial Internet Technology and Its Application in Intelligent Thermoelectric Production", Xia Jiantao, Chairman and CEO of Shanghai Quanying Technology Co., Ltd., brought about the industrialization of thermoelectricity in the era of Industrial Internet. View. He believes that my country's industry has two main problems:

Xia Jiantao, Chairman and CEO of Shanghai Quanying Technology Co., Ltd.

The emergence of the industrial Internet platform can solve the above problems, and it will bring great benefits to the discrete manufacturing industry. The focus is on intelligent management, and for process manufacturing, the focus is on process control. There are three main scenarios for its application in industrial enterprises. The first is to use it in production, the second is to manage the enterprise's data and optimize decision-making, and the third is to realize the optimal allocation and coordination of resources in the entire industry chain. Taking the thermal energy production industry as an example, Xia Jiantao shared how the Industrial Internet is used in the industry and its effects. At the same time, he also mentioned that "massive data + intelligent algorithms + super computing power" will produce intelligent systems that surpass human intelligence and will profoundly change human society.

After the meeting, Yiou New Manufacturing Channel communicated with Xia Jiantao. He said that the current industrial Internet must ultimately be implemented into specific application scenarios. For any equipment or system purchased by an enterprise, he needs to calculate the investment. The output ratio needs to be able to effectively solve existing problems. "Whether an industrial Internet platform or a technology can convince customers depends on whether you can provide customers with tangible and calculable value."

Li Hongfeng, Chairman of Xuanyu Technology, shared about intelligent manufacturing in the 3C industry in the keynote speech "AI Empowers 3C Manufacturing". Xuanyu Technology chose 3C manufacturing as an entry point for intelligent manufacturing because it saw that 3C manufacturing is facing three major difficulties today:

Li Hongfeng, Chairman of Xuanyu Technology

When When an industry faces these difficulties, it must consider transformation and upgrading through technological innovation and cost optimization, which gives rise to their demand for intelligent manufacturing. The 3C manufacturing industry is characterized by, first, a high degree of discreteness, and second, very fast iterations. The advantage of such an industry is that there is a huge value space for efficiency improvements through technological means. The disadvantage is that because it is too discrete, the transformation process is very difficult. Against this background, the path Xuanyu Technology initially chose was to start withMainly domestic enterprises, it is characterized by a relatively good production line foundation and a relatively strong concept, which can drive the entire industry.

He said that smart manufacturing is not automation, but intelligence. In today's technology, smart manufacturing must be a combination of algorithms and computing power. Through data and algorithms, smart manufacturing can be cut into and bring huge value.

Hu Yu, chief scientist of Huilian Infinity, mainly shared the specific application of "Digital Industrial Park", one of the work scenarios of the Industrial Internet of Things, in his keynote speech "Making Industrial Momentum Stronger - Digital Industrial Park 2.0" .

Hu Yu, chief scientist of Huilian Infinity

The value of "Digital Industrial Park" lies in using LPWAN technology to help park managers improve their management level and improve service quality for enterprises settled in the park. He It introduces in detail the architecture of the smart park solution, an overview of the platform, and the methods of utilizing digital operations in actual cases. It also outlines the solutions to the pain points from different roles in the park, hoping to ultimately create a platform that integrates developers, operators and operators of the park. A comprehensive integration platform for businesses, local governments and industry associations.

The core of the Industrial Internet of Things is the integration of information intelligence and industrial intelligence. By using information technology, such as the Internet of Things, big data, artificial intelligence, blockchain, 5G, etc., we can realize the informatization and intelligence of data-driven industrial applications, thereby improving industrial efficiency and creating value. Shang Li, executive director and CTO of Concord New Energy Group and member of the Youth Entrepreneurship Alliance of Future Forum, served as the moderator of the dialogue session with business leaders and scientists on developing the industrial Internet of Things. What are the difficulties? How will the upcoming 5G network era promote the digital transformation of industry and manufacturing? From industrial automation to industrial intelligence upgrading, how industries and enterprises can seize new opportunities and other issues were discussed.

Technological Innovation Dialogue - Industrial Internet of Things: "Intelligent Manufacturing" Upgrade

Hu Yu, chief scientist of Huilian Infinity, believes that the Industrial Internet of Things will continue to move forward in China, but in this In the process, some certainties will be broken, including our industry. He believes that the integration of IT and OT in the Industrial Internet of Things needs to be carried out from two aspects: organizational structure and strategy. In addition, from the perspective of technological innovation in the Industrial Internet of Things, he believes that sensor innovation is very important.

Li Dan, a permanent associate professor and doctoral supervisor in the Department of Computer Science at Tsinghua University, believes that the Industrial Internet of Things is now in a stage of slow growth from concept to implementation, and will get better and better in the future. This is because the technology is mature and the industry’s needs are there. In addition, he believes that the combination of IT and OT will create new opportunities for technological innovation.

Li Hongfeng, chairman of Xuanyu Technology, believes that the industrial Internet of Things must have a gradual and objective law. The integration of IT and OT in the Industrial Internet of Things is the integration of the two. This integration relies onIt is the fusion of "mutual understanding". Information technology people must understand industrial things, and industrial people must understand information technology, and polish and grow on actual projects. Only in this way can we truly increase the number of informatization and information technology in the future. Talent. He believes that data is the foundation for innovation in the Industrial Internet of Things. Without data, there is no support. Data changes from quantitative to qualitative changes, which will lead to application innovation.

Liu Jiangang, managing partner of KPMG China Management Consulting Services, believes that the application of the Industrial Internet of Things is now more than just a concept. How to put the concept into practice? The first is to be demand-oriented; the second is to be strategically driven; the third is to build the company's own capabilities; the fourth is to enter into scenarios; and the fifth is to have the ability to collaborate with the ecosystem. From the perspective of the development of the industrial Internet industry, there must be standards: first, the standard for open industrial Internet interfaces; second, the standard for the integrated IT architecture.

Xia Jiantao, chairman and CEO of Shanghai Quanying Technology Co., Ltd., believes that only a positive and enhanced cycle of the Industrial Internet of Things can truly bring this industry to fruition. The Industrial Internet of Things requires the in-depth integration of IT and OT. It is believed that cloud + terminal innovation is very important to the technological innovation of the Industrial Internet of Things.

Qiming Venture Partners partner Ye Guantai believes that to promote the development of the industrial Internet, a very necessary point is the close integration of IT and OT, but the more important key point is to shorten the chain of interests that connects the entire industry.

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