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Why AI artificial intelligence start-ups fail?
Why AI artificial intelligence start-ups fail?
Although the mainstream concept of the industry thought that AI was a period, not the mouth of the wind, in 2017, everyone was still deeply affected by the wind, and the waves came... The Internet thinking that "pig standing on the air will fly, but AI must meet the wave of entrepreneurship and innovation is one of the few ordinary, shot dead on the beach is common.
The Tencent Research Institute released the "2017 &IT orange with artificial intelligence status and trend of Sino US Venture Capital Research Report" shows, as of June the total number of Sino US artificial intelligence business failures has exceeded 50, confidence this figure by the end of 2017 will be more severe; and it was estimated: artificial intelligence business for two or three years 95% will be closed. The universal law research agency Gartner on "emerging technology maturity curve based on AI technology has been at a critical stage of hope systole and bubble, in accordance with the mainstream concept of industry experts:" closures will be concentrated burst in 2018, the direct reason is the peak period of AI project financing in the first half of 2017, the use of ordinary financing cycle it is about 18 months."
We should not simply pointing losers in the back, let me become a "belated effort" experts, should be a relatively to observers and advocates in the wind just rises.
The discussion and analysis of the problems of AI start-ups will be more practical to find out the real reasons for these business failures. From the perspective of enterprises, valuations, capital, technology and business bubbles will continue to exist. Based on the deepening investigation of a number of artificial Intelligent Company in one year and the continuous exchange of local people, we analyze the main reasons for the failure of these enterprises.
First, the data support of start-ups is lacking. The essence of AI is to imitate human behavior and simulate human intelligence. Therefore, it has a fundamental premise that big data, no big data analysis, big data characteristics to marry big data algorithm learning, is unable to discuss AI. "Artificial intelligence: the way to win in the future" begins, "the Internet has created big data, big data has brought about artificial intelligence." IBM's deep blue computer defeats chess champion Kasparov. Google's AlphaGo defeats the world go champion Li Shishi, all is in the limited machine learning scope, even if go chess's complexity is as high as 10 172 times. But big data often control in Internet tycoons, is not attached to industry giants, it is difficult to have technology break, even with the algorithm or technology is relatively preemptive, but because the application scenarios can not be completed, to experience its true value, will lead to the subsequent failure of financing, capital chain rupture. For example, social media AI management platform Meshfire, video interactive cloud chain, and so on.
Two, the positioning of the entrepreneurial projects shows the phenomenon of pile up. Face recognition, UAV technology is mature, entrepreneur value plate segments of the stampede in, did not find, because there is no technical barriers too high, product differentiation competitive advantage is not obvious, there was the phenomenon of homogeneous competition, business risk increases rapidly; especially in larger companies stationed in or after rolling, investors halfway give up. As the consumer level UAVs Lily Robotics, wearable smart jewelry Vinaya, do open source wearable tracker Angel Sensor, personal library classification based on Shelfie; as well as airlines, zero billion and Parrot are sharply cut; analogy to other companies, like overnight rise of bike sharing some bikes resplendent with variegated coloration. The failure is only a matter of time.
Three. The business of products and technology is not fully understood by the start-ups. The potential customer demand relatively vague understanding of the scene, only pay attention to break in technology, especially the technical team of scientists, from time to time in the R & D investment money, on product sales showed a downturn is not timely to realize the basic reason and make effective adjustment, namely, technology and market is more serious gap. Such as Skye smart UAV, Pearl Automation capital chain rupture, automatic driving to suspend operation; have the impression, the smell of the robot robot restaurant restaurant chains are also operating as dismal, robot attendants only become a gimmick.
Four, the talent structure of the entrepreneurial team is not reasonable. No technical team is very difficult to choose to start or to get financing, technology is the first factor; however, most of the young start-ups is the lack of real understanding of creative and commercial application of a comprehensive marketing personnel, marketing can not be simply astronomical solution for sales, artificial intelligence is highly integrated disciplines, technology not limited to a particular industry and industry, cross-border, blend, and promote the design of business model, the talent request is very high. The most direct example is that the artificial intelligence consumer market has not yet formed the climate, and "should be the rain constant matrix" and "intelligent house of affairs" take the lead in falling. The rule of the investment community, "angel A round", if there is no innovative team structure, will not be loved by the capital.
Appendix: the list of local bankrupt enterprises arranged by the author
The tide of business failure is not the end, but a new starting point for the development of artificial intelligence. This is the opportunity for the entrepreneur, the advisory body, the industry media, and the enterprise.