What's missing from many startups who are standing at the mouth of artificial intelligence and robots? Money should be an important aspect. What are the most important investors? money. The combination of the two, what kind of spark? Unicorn will appear? At the CCF-GAIR conference, the investor's special event was attended by the real-life fund Gu Ziman and several other investors: Hong Feng Capital Wu Feng, Lenovo Star Wu Bingjian, Kun Zhong Capital Yao Haibo and Yun Jiuu Capital Qiu Yan.
(From left to right: Wu Feng, Wu Bingjian, Yao Haibo, Qiu Xin, and Gu Weiman)
Gu Jieman: First introduce your organization and investment so that we can better understand us.
Wu Feng: In the AI field, we established a very famous laboratory in the United States, led by Andrews founder. There are also some companies in the robotics field. In the country, the A-round was the main event, and 360 shots were made. The American beat was also our earliest investment.
Wu Bingjian: We mainly cast angel rounds and A rounds, of which artificial intelligence is an important topic. In the new wave we hope to use the previous investment portfolio to communicate more with entrepreneurs. The second is to hope to connect with investors.
Yao Haibo: We are Kunzhong Capital. We have made early investments in TMT (Technology Media Telecom). Several AIs have voted. We have invested in Sagitar and created UAVs in the United States.
Qiu Xin: I come from Yunjiu Capital and the main team comes from the original China Speedlight and Dexun Investment. Now my personal focus is on deep technology, and a large part of it is artificial intelligence.
Gu Weiman: I am Gu Geman who is a real fund, and it is a relatively early TMT investment institution. We are very concerned about the AI ​​field. This year we are also continuously digging and looking for more excellent opportunities. Investors in the field of artificial intelligence and robotics are very concerned about this year. Let's talk about landmark events to confirm this “spiritâ€.
Qiu Xin: This year's landmark event was Alpha Go. Actually, artificial intelligence put forward a concept very early. In 1997, the American school sentiment was already very hot, but the industry was not particularly hot. This year's Alpha Dog is a result of long-term accumulation. In 2012, research on image recognition, especially in-depth neural networks began. At that time, artificial intelligence gradually entered everyone's perspective. This year's Alpha dog won the Go Master and proved its ability from the public's cognition.
Yao Haibo: I say a phenomenon, what is the outlet? When the valuation of similar companies in China was higher than the valuation of similar companies in the Bay Area, it came to an end. China has more money, more investors, and large industries are diluted. We will look more rationally at AI and technology investments.
Wu Bingjian: High-level talents have already determined their determination to start their own businesses. They all want to come out and venture capitalists are ready for the money. Above the tuyere I think there are a lot of bubbles, typical foam.
Wu Feng: Everyone has finished all sorts of phenomena. What I want to say is the phenomenon we have produced. That is the robot product we have developed in our laboratories.
Gu Weiman: What is the big difference between the AI ​​entrepreneurs in the US market and their counterparts in the Chinese market? In addition to making it easier to get money in the Chinese market, there are no other features to share.
Qiu Xin: There are several aspects. One is whether the United States, whether academic or industrial, invests heavily in AI research and has accumulated a very long time. Therefore, they are more solid on the technical level and have a more solid foundation. And some of our domestic companies are transformed, relatively lacking in technology reserves and a large environment. I think the United States is ahead of the rest.
The next step is the application of artificial intelligence. In the United States, AI covers the vast majority of fields including medical care, e-commerce, advertising, marketing, agriculture, and machinery manufacturing. This direction of image recognition has already been applied to all these industries.
The other is the valuation, the valuation of the American company is far inferior to the equivalent company in the country, because in the early days had already been bought by the big company.
Of course, Chinese AI entrepreneurs should not be pessimistic. Many U.S. companies have offices in China. They know how to get money from investors in the United States, and at the same time they will win many preferential policies and support from the local government. I think this is where our entrepreneurs should learn.
Wu Bingjian: I think that Chinese entrepreneurs want to grow bigger when they start their own business. American entrepreneurs want to ride more. Because China’s algorithmic talent is actually quite impressive and smart enough, it is the goal to be big. In the United States, when the target of the competition is in A-round, only one or two hundred million valuations can be accepted and become a department in a large company...
Gu Weiman: How does AI startup return to practical application and return to the nature of business? How to match technical strength and marketing ability?
Wu Feng: Entrepreneurs may now be technology-driven, but from the perspective of our investment experience, technical advantages may eventually be eroded over time. Nowadays, one characteristic of the entrepreneurial field in the AI ​​field is to cut in from the B-side. At this time, the team's industry leadership, including sales ability, is crucial. However, it cannot be generalized whether it is technology-driven or sales-driven. At this stage, I think that sales ability is very, very important, but in the end it can be determined how big this CEO is.
Gu Weiman: What are your favorite scenarios for AI and robots? Or what kind of field do you want the entrepreneur to enter?
Wu Feng: I have been saying something for the past few days. I think the best scenario in the AI ​​field, or the next company with a market value of one trillion US dollars, I decided to be in the field of automatic driving. For entrepreneurs, we basically judge the four directions: algorithms, high-precision maps, in-car entertainment systems, and onboard security will have some opportunities.
Wu Bingjian: The field of automated driving is also an area I particularly favor, and the second promising area is the financial sector . This area is inherently a data-intensive industry. Every data has been recorded, and each bit efficiency has been increased by hundreds of millions, so this is a better area. In the medical field, I think that there is still a lot of room for the future. It is only that this data has not yet been transmitted to the cloud and many resources are not available.
Yao Haibo: We are also very excited about unmanned driving. In particular, radar is actually the eye of wisdom. At the same time, it is not limited to cars. We see Dajiang’s drones and its eyes are all radar. So we are optimistic about the driverless, robot (including smart robots), the scene is still relatively extensive. In the end, we hope to make smart manufacturing with Chinese characteristics and to have AI with Chinese characteristics.
Qiu Xin: I think the biggest breakthrough in artificial intelligence over the past few years is still image recognition. I think that you can start with an application based on image recognition. There are actually many possibilities for which specific application. I can now see several possible categories:
The first is to subvert what is already there. There may be a huge market right now. Use image recognition to subvert the latest deep learning method.
The second is to extract specific modules into a special scene with a large scene.
Specifically, I think that we should put artificial intelligence and mobile Internet together, it is through mobile applications to achieve this combination, such as some use graphic applications depth learning ability. The wave of mobile Internet is far from over. Internet +, AI +, and deep learning with mobile and AI will be the future.
Gu Weiman: How does the AI ​​start-up team combine technical strength and business operation capabilities? How can the combination and running of the team be better?
Qiu Xin: It is very important to run this thing up, but it is also very difficult. Therefore, when we voted, we valued them more as classmates, alumni, roommates, and fellow villagers...that is, there had been a run-in period before. If two people just knew to let them run in, this is a risk in itself, and there is no good methodology to achieve.
Before we voted for a lot of room, it is now a $ 2 billion valuation. It is a team with two different backgrounds. One is from Tencent and the other is from the traditional real estate industry. So they were able to run in because they were former classmates, and they had had a life and death experience in the Gobi. Gobi Suddenly came back to think about doing this project, three people come together. They are brought together on this occasion.
Yao Haibo: I added a special case. We have voted for a husband and wife company. Both of them are in the United States for 10 years. Men are relatively young. They belong to entrepreneurial scientists; his wife is more lively and is an entrepreneur among scientists. The reason that the two of them combined to give us more confidence is that one person is the leader, that is, his wife has the final say, and then the CTO is him. Of course, this combination will also be affected.
The second example is a team that we previously voted in. The three of them returned from Stanford, and the level of technology is similar. In the end, the founder with higher EQ was elected as the leader of the team. A particularly important point for EQ is to be good at dealing with these localized entrepreneurs, businessmen and the government in China. I hope that the entrepreneurial brothers (especially scientists) will either turn themselves into entrepreneurs among scientists or they will find an entrepreneur as soon as possible to cooperate with you.
Wu Bingjian: We are also very particular about people. Here we would like to share three past investment cases:
The first category is juvenile geniuses. They are two classmates of the same class who start their own business and come forward one step at a time. They then attract some big cows by means of cash and options. The explosive force is fiercer. The second type is a combination of scientists and businessmen. We once voted for a Cambridge professor. He started a venture with his business classmate from Cambridge. He then discovered that on the one hand, he had to do R&D. On the other hand, he had to teach and energy could not be allocated. So the two exchanged positions. The former COO served as the CEO, and then the CEO served as the chairman. The third kind of combination that we prefer is similar to the big companies such as BAT. The technical experts who have really helped these companies earn money. Often they bring out the entire team and have a higher probability of success.
Wu Feng: I think the entrepreneurial team is now divided into four categories: technology, products, operations and business . No matter what kind of core, the CEO can only be classified as a person. The highlight of your body must be higher than the average level of magnitude. The point is the most crucial. As for how to tie in with the matter, it is the four categories, regardless of which category they choose, should be sufficient.
Gu Qiman: I would like to thank several investors for sharing. I have also shared several data with you. Among all listed companies in the United States from 1973 to the present, we will find that 43% of the companies are listed for venture capital. The market value of these companies is 63% of the entire US stock market. So I think that 43% and 63% of such a data side reflects the current era of when we talk about entrepreneurship or business development, it is inevitable to use capital leverage. We are very happy to see today's first-line investors in the mainstream market have in-depth thinking and layout in the AI ​​field. I hope everyone can embrace each other and build a bigger future together.
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