A few days ago, in the basic technology and innovation forum of the 2018 World robotics conference, China Electronics Society released "ten growth technologies of new generation artificial intelligence". After investigation, we visited a number of leading enterprises with leading level and characteristics in the new generation artificial intelligence technology and industry, and visited leading enterprises from well-known universities and colleges Experts and scholars in the field of artificial intelligence of the research institute systematically combed the latest reports of authoritative think tanks and well-known strategic consulting companies, and selected ten most distinctive growth technologies
Antagonistic neural network. It refers to a neural network architecture composed of a neural network module that continuously generates data and a neural network module that continuously judges whether the generated data is true or not, and creates a technology that approximates the real original image, sound and text data. This technology is expected to greatly improve the accuracy and accuracy of machine translation, face recognition and information retrieval. With the improvement of 3D model data sequence ability, it will produce considerable application value in the fields of automatic driving, security monitoring and so on.
Capsule network. It refers to the technology of building multi-layer neuron module in deep neural network to discover and store the detailed spatial position and attitude of objects. This technology enables the machine to quickly recognize the same object in different situations with less sample data. It has broad application prospects in face recognition, image recognition, character recognition and other fields.
Artificial intelligence in the cloud. It refers to the deep integration of the operation mode of cloud computing and artificial intelligence, and the centralized use and sharing of machine learning tools in the cloud. The technology will transfer the huge operation cost of artificial intelligence to the cloud platform, which can effectively reduce the threshold of terminal equipment using artificial intelligence technology, and is conducive to expanding the user group. In the future, it will be widely used in many industries and fields such as medical treatment, manufacturing, energy, education and so on.
Deep reinforcement learning. It is a technology that combines deep neural network and reinforcement learning with decision-making ability to realize the integration of perception, decision-making or perception decision-making through end-to-end learning. This technology has the characteristics of no prior knowledge, reduced network structure complexity and less hardware resource requirements, which can significantly improve the efficiency and robustness of machine intelligence to adapt to complex environment. It will have broad development prospects in intelligent manufacturing, intelligent medical treatment, intelligent education, intelligent driving and other fields.
Intelligent brain computer interaction. It refers to the technology of information interaction and functional integration between the nervous system and external devices by establishing a direct connection path between the human brain nerve and external devices with high biocompatibility. This technology uses brain computer interface controlled by artificial intelligence to accurately analyze the working state of human brain, so as to promote the fusion of brain computer intelligence and make the way of human communication more diversified and efficient. It will be widely used in clinical rehabilitation, autopilot, aerospace and other fields in the future.
Interactive AI platform. It refers to the technology that integrates voice recognition, semantic understanding, natural language processing, speech synthesis and other solutions to provide developers with an open platform with the ability of recognition, understanding and feedback. This technology can realize the natural interaction between machine and human in the dialogue service scene, and is expected to be widely used in many fields such as intelligent wearable devices, smart home, smart car and so on in the future.
Emotional intelligence. It refers to the use of artificial intelligence means to simulate the expression, mood, emotion and other human like emotional response, in order to create a virtual image with emotional attributes. This technology can give machines and devices better ability to recognize, understand and guide human emotions, and bring users more efficient and humanized interactive experience. In the future, it will be more frequently and deeply applied in intelligent robots, intelligent virtual assistants and other fields.
Nerve morphology calculation. It refers to the technology that simulates the biological brain nervous system, simulates the function of biological neurons and synapses and their network organization on the chip, and endows the machine with the ability of perception and learning. The goal of this technology is to make the machine have the characteristics of low power consumption, high efficiency and high fault tolerance similar to biological brain, which will have broad application prospects in intelligent driving, intelligent security, intelligent search and other fields.
Meta learning. It refers to the technology that combines neural network with human attention mechanism to build a general algorithm model, so that machine intelligence has the ability of fast autonomous learning. This technology can make machine intelligence realize autonomous programming, and significantly improve the efficiency and accuracy of the existing algorithm model. The further application in the future will become the key to promote the artificial intelligence from the special stage to the general stage.
Quantum neural network. Quantum devices are used to build neural networks and optimize the structure and performance of neural networks. This technology makes full use of the characteristics of quantum computing such as ultra-high speed, super parallel and exponential capacity, and effectively shortens the training time of neural network. In the future, it will have important application value and broad prospects in face recognition, image recognition, character recognition and other fields.
At present, the world is experiencing a new round of changes with high coupling and deep superposition of science and technology and industry. The formation of big data, the innovation of theoretical algorithms, the improvement of computing power and the evolution of network facilities drive artificial intelligence into a new round of innovation and development peak. New technologies continue to make breakthrough progress, showing deep learning, cross-border integration, human-computer cooperation, open intelligence of the group, and the development trend of network infrastructure Autonomous Control and other new application-oriented features. It will provide intellectual support with decision-making reference value and practical significance for the healthy development of the industry, orderly entry of funds, introduction of policy planning and development of emerging markets by strengthening the foresight prediction of the new generation of artificial intelligence technology and accurately grasping the dynamic and development trend of global technological innovation.


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