Since 2020, as the development of AI has begun to move toward product and industry integration, the commercial revenue brought by AI has become a measure of a technology giant’s comprehensive strength in technology strategy, product planning, ecological construction, etc. The key indicators are based on this.
In the context of the continued expansion of the digital economy, business entities from all walks of life are faced with the urgent need to use digital technology solutions to achieve transformation. This will further promote the vigorous development of artificial intelligence. Thanks to the continuous drive of digital technology progress and business model innovation, as well as the increasing willingness of traditional industries to transform and upgrade, digital transformation and development have become a general trend today, and the blessing of artificial intelligence has become an inevitable situation.
As the data base brought about by industrial digitization becomes increasingly mature, AI is developing in terms of training layer (learning ability), perception layer (information receiving ability), and cognitive layer (information analysis ability). The technologies have matured and have now officially entered the stage of industrial benefit transformation for practical applications. At the same time, rich industry practices have enabled artificial intelligence to have richer application scenarios, such as risk control assessment, engineering operation and maintenance, biopharmaceuticals, and logistics and freight. etc., rich application scenarios have also accelerated the structural upgrade of the AI industry.
How to organically integrate AI and industry implementation? How should the development of downstream applications of artificial intelligence be practiced? AISummit's "AI Empowering Industrial Practice" special event is not to be missed!
On August 6-7, 2022, the AISummit Global Artificial Intelligence Technology Conference will be held as scheduled on the official website of the conference in the form of an online live broadcast. It is expected to be 10 Thousands of people attended the meeting. With the theme of "Drive·Innovation·Digital Intelligence", this conference is mainly aimed at mid-to-high-end technology managers and technical practitioners of technology companies, business managers planning/currently undergoing digital transformation, and people interested in the field of artificial intelligence. and entrepreneurs. The conference will also invite nearly a hundred technical elites from well-known Internet technology companies, managers of traditional companies in the digital-intelligence transformation period, and experts and scholars from cutting-edge academic institutions to jointly discuss the industry driving forces of artificial intelligence and discuss cutting-edge innovations in artificial intelligence. Technology, let’s talk about the wave of “digital intelligence” in the era of artificial intelligence.
At this AISummit conference, the "AI Empowering Industry Practice" special session was attended by many industry veterans from Ant Group, Baidu, Taifan Technology, Yunzhihui, Fuyou Trucks, etc. Technical leaders and experts share advanced cases and technical thinking on AI-enabled industrial practice from the perspective of business practice.
In cloud-native large-scale online microservice systems, failures mainly come from changes and capacity. The occurrence of failures may cause service interruptions and production accidents, thereby causing huge losses. Economic losses and concentrated customer complaints. We apply algorithm models to build change risk identification and automatic capacity assessment to improve the reliability of the Ant system and ensure high availability.
Change risk identification: Automatic monitoring detects fluctuations in batch change indicators, effectively intercepts abnormal changes, and significantly reduces change failures
Automatic capacity assessment: Automatically evaluate the resource requirements of online applications, accurately guide the expansion and contraction of online applications, and effectively balance costs and risks.
In this sharing, Jiang Wei, head of the risk intelligent high-availability algorithm of Ant Group’s Technology Risk Department, will bring Ant Group’s practice in green intelligent capacity technology. Its risk identification and capacity assessment are reliable in the system. Remarkable results have been achieved in terms of safety and security.
In recent years, "AI medical care" has developed rapidly. With its intelligent and automated characteristics, it is mainly used in public health, hospital management, medical imaging, medical robots, drug research and development, health management, and precision medicine. and medical payments. Although "AI medical care" is still in its early stages, with relatively low commercial application and low overall market penetration, "AI medical care" has a very broad space for development. AI can not only assist the management and research and development of hospitals and pharmaceutical companies, but also help medical institutions improve the level of medical modernization and meet residents' growing medical care needs.
In this sharing, Fang Xiaomin, Baidu’s senior R&D engineer and head of AI drug discovery technology, will bring Baidu’s new results in drug discovery and research using biocomputing large models. This technology can complete compound modeling and Protein modeling and folding, and achieved remarkable results.
As the vertical application of artificial intelligence in industrial practice becomes more and more profound, AI technology seems to have encountered double bottlenecks in theory and implementation when overcoming the "neck choke" problem in hundreds of industries.
This sharing was conducted by Ma Guoning, deputy general manager of Taifan Technology, starting from the knowledge graph, an important technology in the field of cognitive intelligence, and the famous Königsberg Seven Bridges Problem proposed by Euler. It extends to how to use cutting-edge theoretical technologies in graph theory and other fields to solve the problems of complex entities, difficult retrieval, and excessive update overhead faced in the practical application of knowledge graphs; it also introduces how to create an effective platform tool to achieve low-cost, It solves different industry problems in a highly efficient way; and finally demonstrates the various possibilities and directions generated by AI and industrial empowerment. The artificial intelligence industry has a future where a hundred flowers bloom.
In recent years, AI has been widely used in various industries, promoting the intelligence of various industries, and greatly improving the level of management and decision-making, including the IT industry itself. The application of AI to IT operation and maintenance, also known as AIOps, is a hot spot for AI application in the IT industry. The reasons behind this are not difficult to understand: on the one hand, as IT systems become increasingly close to business, especially in many enterprises where IT is the business (such as banks), IT and business are no longer separated, and the importance of IT is self-evident; on the other hand, On the one hand, IT systems are becoming more and more complex, and their management is becoming more and more difficult. How to operate and maintain efficiently has become a problem that IT departments and even CIOs must face, especially for large data centers. AI technology is considered an effective solution to this problem and is rapidly gaining popularity.
In this sharing, Zhang Bo, CTO of Cloud Intelligence, will share about the intelligent operation and maintenance of the AI2B industry. He will explain how AI algorithms are adapted and implemented in the industry and how AI engineering can be implemented in the industry. Adaptation and implementation were explained, and practical cases of enterprise development technology in the industry were shared.
"AI transportation" refers to the use of artificial intelligence, Internet of Things, cloud computing, big data, 5G and other technologies in multiple transportation links such as transportation system management, travel navigation, and in-car interaction to achieve intelligent transportation, thereby Improve urban transportation convenience, increase road traffic speed, and optimize the interaction experience between people and vehicles.
In terms of travel navigation, AI can rely on real-time road data information to grasp route conditions, historical driving time and other data, and calculate the best route through the analysis of massive big data. Travel plan.
In this sharing, Chen Guanling, technical partner of Fuyou Trucks, brought about the technological application of AI-empowered trunk logistics, that is, autonomous driving, in the logistics industry. He shared that there are many long-term pain points in road freight, and It explained the practical application of autonomous driving in port operations in closed scenarios, and conducted a detailed analysis of the challenges and advantages of L4 autonomous truck technology. Finally, it shared open source commercial operation scenarios for autonomous driving companies, truly focusing on technology, implementation, and The integrated development of AI and logistics was comprehensively analyzed from three practical perspectives.
Click to enterAISummit Global Artificial Intelligence Technology Conference Official website, follow the prompts to complete the registration and submit the information.
Scan the QR code to join the official group of the conference, participate in the lottery, and win exquisite gifts such as SONY speakers, Bingdundun, and AI technology books, as well as red envelopes and raindrops
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