Recently, the Institute of Computing Technology of the Chinese Academy of Sciences (hereinafter referred to as the Institute of Computing Technology of the Chinese Academy of Sciences) released the world's first "neural network" processor chip capable of "deep learning", called "Cambrian". Dr. Chen Tianshi, one of the heads of the research group and the Institute of Computing Technology of the Chinese Academy of Sciences, revealed that the results will be officially put into industrialization this year. In the near future, anti-fraud brush pay, image search, etc. will be more reliable and easy to use.
Not long ago, a Go program "AlphaGo" developed by Google Inc. defeated Korean player Li Shishi 4:1. The secret of "AlphaGo" is to imitate the "deep learning" of human beings through neural networks.
“Deep learning refers to multi-layered artificial neural networks and methods of training it. Popularly speaking, computers refer to the mechanism of human brain through deep neural networks to simulate, judge, and make decisions. In recent years, this method has been applied to many Fields, such as face recognition, speech recognition, etc., will be a hot research direction in the field of artificial intelligence in the near future and in the future," said Yi Jianqiang, a researcher at the Institute of Automation, Chinese Academy of Sciences.
Chen Tianshi said that "deep learning" can be developed to the present stage, benefiting from the improvement of the computing power of computing systems, and this improvement is the result of the explosive development of processors as technical support. Currently, the processor used by "AlphaGo" is a CPU processor that is common in other fields. In 2010, Google used 16,000 processors to run for 7 days to train a deep learning neural network that recognizes cat faces. In the game of Go, the human "AlphaGo" needs more processors. Ordinary people want to use this. Technology is impossible.
“Ordinary processors are like Swiss Army Knives. Although they are versatile, they are not professional. If chefs want to make decent dishes, they must use professional kitchen knives, and the specialized deep learning processor is more efficient and faster. 'Chopper'." Chen Tianshi said.
The deep learning processor is to create a chip for the computer that mimics the multi-layer artificial neural network of the human brain. In the operation of the deep learning processor, the computing power of the computing system is the key to determining the efficiency of deep learning processing. The "Cambrian" processor released by the Institute of Computing Technology of the Chinese Academy of Sciences is two orders of magnitude better than the processor used by "AlphaGo", which means that it can make artificial intelligence run faster and further.
According to Chen Tianshi, this year's research group and the Institute of Computing Technology of the Chinese Academy of Sciences have already hatched the Chinese Academy of Sciences, and officially started the industrialization of scientific research results. The future application aims at three high-performance servers, high-performance terminal chips and robot chips in enterprises and research institutes to realize more functions. For example, taking a photo with a mobile phone knows who the photo is, and can intelligently classify many videos. The image search will be more accurate and easy to use. Just take a tree on the side of the road and you can search for this tree. All the information, not just the current text search. According to reports, the future areas of the "Cambrian" service can include both social and people's livelihood as well as major national needs.
In the eyes of many artificial intelligence experts, although artificial intelligence has made great progress after nearly 60 years of development, it is still in the early stage of development, and it can still be described as “innovativeâ€. “Currently, special-purpose artificial intelligence technology for specific fields has made breakthroughs, and can even surpass human intelligence in single-point breakthroughs and single-level tests at local intelligence levels. For example, Japanese humanoid robots, American cheetah robots, German industrial robots, and China's face recognition, iris recognition, etc., said Tan Tieniu, an academician of the Chinese Academy of Sciences and vice chairman of the Chinese Society of Artificial Intelligence.
In the view of Xu Yangsheng, academician of the Chinese Academy of Engineering and president of the Chinese University of Hong Kong (Shenzhen), in the past few decades, scientists have concentrated more on the research of robot movements, allowing robots to climb, grasp, and move like humans. Jump and so on. Xu Yangsheng made an analogy: In the first 50 years, we studied the robot "wearing" action, but did not let the robot learn the perception and cognitive ability such as "do not wear clothes."
With the development of computer and Internet technologies, companies such as Google and Baidu have successively launched deep learning programs such as “AlphaGo†and “Baidu Brain†to promote the continuous improvement of artificial intelligence. Tan Tieniu said that the future research of artificial intelligence needs to be deeply integrated with the disciplines of brain and neuroscience, cognitive science and psychology. (Reporter Wu Yuehui)
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