Nowadays, the “smart +†society is approaching, and all sectors of society are actively sketching the future social picture. Foreign artificial intelligence giants are constantly moving, and there are many breakthroughs in basic technology and application fields, which can be summarized into three points: strong basic research capabilities, intensive cross-border innovation, and continuous use of talent dividends.
China has outstanding strength in the fields of deep learning and recognition technology, and is at the forefront of the world in the application level of artificial intelligence market. However, there are shortcomings in basic technology, cross-border collaboration in the industrial chain, and core talent training. Industry experts have called for the future of China's artificial intelligence industry and academic circles to focus on the above three weaknesses, reviewing the situation, considering the whole situation, grasping the plan, and solidly advancing, while consolidating the existing advantages, complementing the shortcomings and promoting the sustainable development of China's artificial intelligence industry. .
The basic layer is researched into artificial intelligence "hard indicators"The research of artificial intelligence can be divided into the basic layer, the technical layer and the application layer. The United States has continuously made research and practical progress in the technical layer with high technical difficulty and strong technical driving effect; while China has weaker ability in the basic layer, in the technical layer. And the application layer is more powerful.
The basic layer mainly refers to the core capabilities of processors and chips supporting artificial intelligence technology; the technical layer includes general-purpose technologies such as natural language processing, computer vision, and technology platform; and the application layer refers to practical applications such as automatic driving and intelligent robots.
The rise of the artificial intelligence wave has led large American companies to enter the basic layer of research. Take the chip as an example. NVI, the US chip manufacturer, launched the world's first 120 trillion sub-processor Volta V100 GPU, which can reduce the efficiency of machine learning instructions from a few weeks to a few hours, helping customers to be faster. Iterate and optimize the time to market for each product. In the past three years, Nvidia has provided 10 times the performance acceleration for deep learning. It has been called “the square of Moore's Law†by the critics, maintaining the current performance improvement rate. By 2025, the GPU will be 1000 times faster than the CPU. performance.
Companies such as Google, Amazon, Microsoft, and Apple, which did not initially develop chips, have begun to work on chips and processors, which has further strengthened the US's research position in the global artificial intelligence infrastructure. Microsoft announced its artificial intelligence chip manufacturing project and demonstrated a new chip specifically for Microsoft's augmented reality glasses HoloLens. Google announced the development of its deep learning chips in 2016 and claimed that with the outbreak of speech recognition technology, the high-performance processor TPU has saved the company the cost of creating 15 new data centers. Google is also working with biotech companies to develop chips that efficiently calculate DNA information. In April 2017, Apple announced that Apple will further master the industry chain's dominance through independent research and development and production of chips. As soon as the news came out, the share price of Apple chip supplier UK company ImaginaTIon plunged.
However, China still lags behind US companies in the field of chip-based R&D, and the demand for imported chips remains high.
Xie Yinan, general manager of the brand and market center of the Chinese company "Computer Technology", said that in the field of image recognition, the company also uses NVIDIA and Intel chips, and no domestic chips can be completely replaced. Song Jiqiang, president of Intel China Research Institute, also acknowledged that the shortcomings of China's artificial intelligence field are that our original theoretical innovation and basic artificial intelligence research and development capabilities are not enough. Chinese scholars need to make breakthroughs in theory. Yu Kai, the founder of Horizon Robotics, said that in the era of PC and mobile Internet, we have missed basic platform technologies such as operating systems, and the era of artificial intelligence needs to catch up.
The China Electronics Society released the "China Robot Industry Development Report" pointed out that China's robotics field core technology accumulation is insufficient, capital investment is relatively limited and scattered, high-end market has long been occupied by foreign-funded enterprises, largely relying on imported parts and components assembly, set Becoming a main business, although there are certain breakthroughs, it is basically passive and follow-up development, and it is difficult to obtain the initiative of industrial development.
Yao Zhizhi, the only Chinese winner of the computer science and Turing Awards, said that China wants to achieve the strategic goal of the world's major artificial intelligence innovation center in 2030. First, it must solve the problem of lack of theory in the development of artificial intelligence. In the next wave of artificial intelligence development, China should achieve some original and intellectual property achievements, rather than catch up with the technology invented by others.
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