The rapid development of artificial intelligence, not only artificial intelligence technology has been improved, but also has a certain impact on the development of enterprises and people’s life and work. In order to better use and understand artificial intelligence, it is necessary to understand the development status and prospects of artificial intelligence.
Deeply understand the development status and prospects of artificial intelligence
As application and business models take shape, the ai industry will continue to grow. With more than 2,500 AI enterprises in China, it has become one of the major concentrations of unicorn enterprises in the world. In 2021, the degree of specialization and differentiation in the field of ARTIFICIAL intelligence will be further enhanced, and the commercialization stage of the widespread application of ARTIFICIAL intelligence will come to the ground.
First, deep learning technology develops from single mode to multi-mode.
In the future, signals that are difficult to quantify, such as smell, taste and psychology, can even be fused to realize joint analysis of multiple modes, so as to upgrade deep learning from perceptual intelligence to cognitive intelligence and assist human work in more scenes and more businesses. On the one hand, multi-mode fusion can promote the upgrading of human-computer interaction mode. In the process of human-computer interaction, the emotion and expression semantics of the machine can be experienced from the visual, auditory and tactile aspects, and the naturalness and accuracy of human-computer interaction can be improved as a whole through the multi-way interaction of text, speech and action. On the other hand, the multi-modal fusion technology can simulate the form, expression and function of the human body to create a highly anthropomorphic virtual image, communicate and interact with people like real people, and constantly improve the interactive experience.
Deeply understand the development status and prospects of artificial intelligence
Second, the rise of edge artificial intelligence.
Edge AI is one of the high-profile new areas of AI that aims to let users run AI processes without worrying about privacy or the impact of slower data transfers. Edge AI could make AI technology more widely available, allowing smart devices to respond quickly to input without needing to access a cloud platform.
Edge AI is becoming more and more important because more and more devices need to use AI technology when they don’t have access to cloud platforms. In applications such as automated robots or smart cars equipped with computer vision algorithms, the lag in data transmission can be disastrous. Autonomous vehicles cannot be affected by delays when detecting people or obstacles in the road, and because fast response times are so important, edge AI systems must be employed that allow real-time analysis and classification of images without relying on cloud computing connections.
Third, ARTIFICIAL intelligence will present the trend of multi-platform and multi-system collaboration.
In the future, the AI industry will step towards industrialization. Standardized products, large-scale production and assembly line operation will be the development direction of ai industrialization. A large amount of human-machine collaboration experience accumulated in enterprise industry practice will spread to more industries through open platform. Enterprises with both industry knowledge and intelligent technology empower horizontal multi-industry scenarios by providing standardized and modular products and services. “Openness and sharing” will be the key words in the development of ai industry in the next stage.
Deeply understand the development status and prospects of artificial intelligence
Fourthly, human-machine collaboration will become a new mode of industrial development in the future.
In the first development stage of artificial intelligence initiated by deep learning technology, the innovation of single point technology rapidly forms a small closed loop of technology application in the market, and a technology-driven business model is rapidly formed. Breakthroughs in core ai technologies such as computer vision, natural language processing and speech processing have ushered in a new wave of global intelligence. Taking computer vision as an example, scene problems such as access control, attendance, identity check, face brushing and payment can be effectively solved after the application of computer vision technologies such as living detection, ReID and action recognition. However, with the deepening of the application of artificial intelligence technology in the scene in the future, the closed-loop technology realized by a single technology is difficult to meet the intelligent requirements in complex scenes. People’s requirements for intelligent algorithms continue to rise, and the research and development of core technology capabilities becomes more difficult.
At present, artificial intelligence has been in the financial, medical, education, retail, industry, transportation, entertainment and many other fields for intelligent penetration. Under the trend of intelligent transformation, traditional industries have begun to explore how to combine artificial intelligence with application. With the gradual deepening of the intelligent practice of traditional industries, in-depth knowledge and experience in the industry is particularly important. Simple artificial intelligence technology overlay will no longer meet users’ intelligence expectations. For example, in the financial field, fake applications, fake transactions and content violations have caused great risks to traditional financial credit. Traditional user credit evaluation has made the application process of enterprise and individual credit more complicated, and financial institutions have insufficient risk control. Man-machine coordinated ability through fusion expert with the machine, the risk control model of expert knowledge skills, structured, and then using the deep learning, natural language processing, computer vision, knowledge map and other technology to automatically learn the behavior of borrowers consumption details, precision positioning, a picture of the user, so as to improve the ability of risk identification, risk of global do effective control.
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