The Future and Development of Artificial Intelligence Industry
After the topic of industrial control, today let's talk about artificial intelligence from a special point of view, which seems a little far from PCB manufacturing.
How to realize the leapfrog development from special artificial intelligence to general artificial intelligence is not only an inevitable trend in the development of next-generation artificial intelligence, but also a major challenge in the field of research and application.
From artificial intelligence to the development of human-machine hybrid intelligence. Drawing on the research results of brain science and cognitive science is an important research direction of artificial intelligence. Human-machine hybrid intelligence aims to introduce human functions or cognitive models into artificial intelligence systems, improve the performance of artificial intelligence systems, make artificial intelligence a natural extension and expansion of human intelligence, and solve complex problems more efficiently through human-machine collaboration . In my country's new generation of artificial intelligence planning and the American Brain Project, human-machine hybrid intelligence is an important research and development direction.
From "artificial + intelligence" to the development of autonomous intelligent systems.At present, a large amount of research in the field of artificial intelligence focuses on deep learning, but the limitation of deep learning is that it requires a lot of manual intervention, such as manually designing deep neural network models, manually setting application scenarios, manually collecting and labeling a large amount of training data, and users need manual adaptation. Intelligent systems, etc., are very time-consuming and labor-intensive. Therefore, researchers have begun to pay attention to autonomous intelligence methods that reduce manual intervention and improve the autonomous learning ability of machine intelligence to the environment. For example, AlphaGo, the follow-up version of the AlphaGo system, starts from scratch and realizes the "general chess artificial intelligence" of Go, chess, and Japanese chess through self-play reinforcement learning.