introduction Since the birth of "thoughtful machines" in the 1950s, software developers have been trying to teach computers how to think like humans. However, in the next few decades, the development of artificial intelligence (AI) has remained in a gradual linear growth. Advances in related technologies are often accompanied by stagnation and frustration because of the high development costs and the lack of sufficient data to support artificial intelligence algorithms. However, in the past decade, computing power has increased dramatically, deep learning algorithms have been continuously improved, machine learning has become more powerful, and the rapid increase in data volume has greatly promoted the development of these algorithms. Artificial intelligence has since accelerated growth. The new stage. After more than 60 years, the development of artificial intelligence is close to the critical point, and it has the potential to realize large-scale commercial use. However, our latest study shows that the rapid development of artificial intelligence may be more conducive to the technology sector, because the industry has the relevant talent, technology and capital, and it is easier to promote the development and popularization of artificial intelligence. In contrast, China's traditional industries are not ready to use artificial intelligence technology, and most of them have not yet regarded it as a strategic focus. Key term Artificial intelligence is the theory and development of computer systems that can replace human intelligence to perform tasks that are typically performed by the latter, such as visual perception, speech recognition, decision making, and language conversion. Machine learning is also an artificial intelligence that allows computers to learn without explicit programming. Machine learning focuses on developing self-learning computer programs that grow and change as new data is encountered. Deep learning is a function of artificial intelligence. It mainly processes data by imitating the working mode of the human brain and generates patterns for decision making. Deep learning is a subset of machine learning in artificial intelligence. Deep learning has a network that can learn from unstructured or unlabeled data without any supervision. To better understand the potential impact of artificial intelligence on traditional Chinese industries, we recently conducted a survey of 80 companies. Of these, 60 are in traditional industries such as retail, heavy industry and construction. In addition, the survey also included 20 artificial intelligence experts from China's leading Internet companies, including several startups. The survey covers a wide range of industries, including financial, healthcare, retail, consumer goods, technology, media and telecommunications. A small percentage of respondents agree that artificial intelligence can be a disruptive force in their industry. Although the pace of change may vary from industry to industry, 90% of respondents believe that artificial intelligence will fundamentally change their industry. When asked how artificial intelligence can make an impact, respondents proposed more than 100 potential ways, from application development to improve operational efficiency to new product and service development. Despite the dawn of artificial intelligence, our research shows that traditional industry companies are still struggling and hesitant to invest in this technology. More than 40% of survey respondents said that their CEOs did not focus on artificial intelligence, and more than 60% believe that their company's artificial intelligence strategy has not made satisfactory progress in the past year (see figure 1). figure 1: Illustration: For traditional industries, 40% of companies still have no artificial intelligence as a strategic issue; 60% of traditional industry experts believe that artificial intelligence technology has been slow in their companies in the past year. In the survey, most executives pointed out that lack of talent is the main obstacle to the development of specific artificial intelligence strategies. In fact, less than 25% of China's artificial intelligence practitioners have more than 10 years of industry experience, compared with 50% in the US. A CTO said that there are only a handful of Chinese institutions of higher learning that offer machine learning related majors. Even if you have a major, most students develop applications that don't really work in real life. In view of the above challenges, respondents in the traditional industry believe that the prospects for success in this field are not optimistic: 84% of respondents said that the biggest winners of artificial intelligence may be Internet companies and startups, not the current ones. Industry leader (see Figure 2). figure 2: Illustration: At the same time, 60% of the experts surveyed believe that large Internet companies are most likely to lead the development of artificial intelligence technology in the industry in which the company is located. Artificial intelligence reaches the critical point of the outbreak With the technological breakthrough and the continuous expansion of application opportunities, artificial intelligence has reached the critical point of large-scale application. The four major trends show that artificial intelligence will bring disruptive changes to all walks of life: image 3: Graphic: Core computing technologies, algorithms, data sets, and applications have made significant progress, pushing artificial intelligence technology to the "burst point." 1. Leading semiconductor manufacturers, CPUs and GPU companies regard artificial intelligence as their core goal, investing heavily in processing technology to lay the foundation for artificial intelligence and machine learning. 2. The number and scale of open source artificial intelligence platforms continues to soar, and developers are free to use the programming interface to build artificial intelligence using a variety of tools, algorithms, and training data. 3. The size and variety of data resources has also increased significantly, meaning that machines can be trained to make faster and better decisions (see Figure 4). 4. High-tech giants and venture capital institutions are eager for startups committed to “innovative applications of artificial intelligence across industriesâ€. From 2010 to 2014, the amount of venture capital invested by artificial intelligence startups increased more than 20 times. Figure 4: Illustration: The generation and collection of complex data is exploding, and the data sources are very diverse. We are no stranger to this historic turning point. When technological innovation and market forces come together, they create products that are sufficient to reverse the situation in the industry. The release of the iPhone iPhone in 2007 is such a historical moment. When the sophisticated technology of touch screens is intertwined with the growing popularity of mobile phones, new products are created that are transforming the entire industry. Although the exact time is still unpredictable, artificial intelligence seems to have reached a similar explosive historical turning point. Significant technological advances in artificial intelligence have created numerous opportunities that will lead to products and services that change the rules of the game. One of the key applications is speech recognition. The success rate of natural language processing is close to 99% (technical tipping point), and large technology companies around the world and China are working hard to introduce corresponding home network equipment, such as routers with voice input technology (see Figure 3). In the field of unmanned driving, key technologies are also approaching critical points: for example, the target tracking algorithm, the algorithm used to identify targets near the vehicle, has reached 90% accuracy. For example, solid-state laser radar is also available (similar to radar, but with a laser as a working beam), which can be used to collect high-frequency data from the surrounding environment of the vehicle. As these technologies quickly enter the mature and feasible stage, various large technology companies, such as Google, NVIDIA, Intel and BMW, are rushing to develop autonomous vehicles. Voice processing technology is also approaching the "burst point", which will redefine the way human-computer interaction, voice assistants and smart home products are ready to go. Figure 5: China will lead the industry trend Although the development of artificial intelligence is mainly driven by global high-tech companies, Chinese companies are also committed to becoming leaders in this emerging field. For example, China's creation of the local semiconductor industry mainly emphasizes the development of CPU and GPU technologies on which machine learning depends. Baidu has become the leader in the speech recognition market with 96% accuracy, catching up with even competitors such as Google, Microsoft and Amazon. It is expected that China's artificial intelligence application market will grow at a rate of 50% year by year, far exceeding the compound annual growth rate of 20% in the global market. The Chinese government has determined that artificial intelligence is a new engine for economic development, so it invests in academic research and provides economic incentives for artificial intelligence companies. China's Internet giants view artificial intelligence as a key point, and startups continue to develop a variety of human intelligence applications, including robotics, healthcare, and drones. Some Chinese companies (such as NIST's HKUST and Imagenet's Hikvision) have even surpassed the world's leading competitors in artificial intelligence technology. The challenge to traditional companies: becoming a leader in the industry or behind others China actively promotes the revolution of artificial intelligence, which brings certain difficulties to domestic non-tech enterprises, because the latter will have to start using artificial intelligence technology. Many of these traditional companies have begun to work with Internet companies in the field of artificial intelligence applications to increase their chances of success. In this collaborative process, they provide valuable proprietary data and industry experience for potential opponents in the future. Working with companies that might destroy themselves, just as they impact banks, businesses and other industries, can they really help traditional companies succeed? Is high-tech companies the only winners of China's artificial intelligence boom? For traditional enterprises, if they do not cooperate, the other strategies that can be adopted are: investing funds and joining the competition of artificial intelligence technology and capabilities. However, given that we predict that the future development of the artificial intelligence industry carries a lot of uncertainty, it may be unwise to rely solely on forecasting for these initiatives. Can China's advantage in the field of artificial intelligence be fully utilized by domestic traditional enterprises? CEOs need to answer nine questions about artificial intelligence strategies For artificial intelligence, most traditional Chinese companies do not take a “laissez-faire†attitude strategically. The CEOs of Chinese companies must actively think about this issue and make prudent strategic decisions: whether to “develop and growâ€, “build cooperationâ€, or just adopt a “wait and see†attitude. The following are the nine major questions that business leaders need to answer when developing an artificial intelligence strategy (see Figure 6). Figure 6: In the face of tremendous changes and fierce competition, CEOs of traditional industry companies must answer the following nine questions in order to achieve a leading position in the field of artificial intelligence. What stage are we in now? 1) What is the stage of adopting artificial intelligence technology in our industry? Are we using artificial intelligence-based applications now, or are we in the initial stages of applying artificial intelligence to our business? 2) Who is in the industry we are leading the use of artificial intelligence technology? Is our company a leader or a follower? What are the best practices that our company can learn from? 3) Are our organizations ready to develop and adopt an artificial intelligence strategy? What are the foundations for the full adoption of artificial intelligence in the company? What is our target competitive field in the future? 4) What are the feasible artificial intelligence application cases in the industry in which our company is located? What are the key technologies and which companies can enter the industry we are in? 5) What are the business results of artificial intelligence in the near and long term? How long is the investment in artificial intelligence expected to return? What are the expected trade-offs when deciding on the timing of investment? 6) How should we use artificial intelligence to enter or create new areas? Artificial intelligence applications provide capabilities that go far beyond current specifications and may motivate companies to extend their current focus to other areas. How will artificial intelligence change the rules of competition and the competitive landscape of our company? What artificial intelligence capabilities do we need and how do we acquire them? 7) What artificial intelligence capabilities should we use? Based on our analysis of potential cases and the competitive impact of artificial intelligence, what technical and commercial talents do we specifically need to implement our goals? 8) How can we acquire the above capabilities? Is it outsourcing, cooperation, or self-construction? Each option has potential advantages and disadvantages. 9) How should we use these capabilities to create a continuous innovation process? Companies must be able to predict how these capabilities will drive growth in the future to maximize the use of artificial intelligence investments. For companies in the traditional industry, the question is not whether they should consider using artificial intelligence applications in their own business and strategic processes – rather, what artificial intelligence strategies they should develop and how to implement them. Chinese non-high-tech companies can either learn from domestic high-tech companies or watch each other take the lead in the technology industry. In order to avoid backwardness or worse, CEOs must actively consider the current situation and potential future of artificial intelligence in their industry, clarify the focus of future goals, and build an engine that discovers and captures the benefits of artificial intelligence in the industry. Stack Battery,Saft Lithium Batteries,Stacked Lithium Battery,Solar Lithium Battery JIANGSU BEST ENERGY CO.,LTD , https://www.bestsolar-group.com
