Sequoia China recently released an article featuring an interview with their Partner Yue Ji on his framework for thinking about AI investments and how he's applied it to Sequoia's current portfolio. It covers AI's application in a number of industries, why Sequoia focuses its AI investments on clear use cases, the current AI talent gap, and the winner-take-all nature of the technology.
"Why have we been optimistic about our investment in Guazi (a C2C used car trading platform), and kept increasing our share in the company? Because Guazi can get data from its users during transactions, and conduct deep learning based on those data, to improve the consumer experiences in the future", Yue Ji, the Partner of Sequoia Capital China, said. Guazi has become one of the typical cases in Sequoia China's AI portfolio.
Why typical? Because the investment in Guazi matches two primary considerations of Sequoia's investments in AI. First, the company should have real use cases and address real world problems. And second, the system should have the ability to improve itself through a continuous stream of data.
Recently, in an interview with PE Daily, Yue Ji gave a detailed explanation of Sequoia China's AI map. He has been in charge of or involved with the investments in a series of outstanding companies, such as Dianping, ele.me, Tuniu, Ganji.com, Noah Wealth Management, Maple Leaf Education Systems, and more. In recent years, Yue Ji and Sequoia China have reaped large returns from their AI investments, including with Guazi, 4Paradigm, Zuoye Bang, Patsnap, Cloudwise, Sensors Data, Infervision, and Ping++.
Behind the investments made by Sequoia lies one rule: the business plan for this AI application must be feasible. Lots of AI startups are holding a hammer and looking for nails. They do not know about traditional industries and are not aware of the pain point in those industries. Whether or not those nails exist is the problem the people holding the hammers have to think about carefully.
What does the AI Investment Map of Sequoia Capital China look like?
Security --- Yitu Tech, DeepGlint, Mininglamp
Finance --- 4Paradigm, JD Finance, 100Credit.cn, Ping++
Media / Information --- Toutiao, Kuaishou, Miaopai
Domestic Service --- Meituan, ele.me, JD Dada, WINNER Technology（汇纳科技）
Transportation --- NextEV, Didi, Mobike, PonyAI, Guazi
Healthcare --- Infervision, Voxel Cloud, Synyi
Hardware --- DJI, Ninebot, Horizon Robotics, Chumen Wenwen
Technology --- Cloudwise, Patsnap, Sensors Data
Those companies are the bellwethers in their corresponding fields. For instance, Toutiao's automated news recommendation app uses AI to generate content for around 700 million users. The AI product provided by Infervision could reduce the average amount of time needed for CT image analysis from around 15 to 30 minutes to just a few seconds. The electric car from NextEV, the ES8, is ready for mass production. Combined with Didi and Mobike, Sequoia Capital China's investments in the transportation industry have also changed the way people get around in China.
Artificial Intelligence industry could be divided into three dimensions: fundamental research, technology and applications. Sequoia Capital China is currently focusing more on the application level.
“The expansion of artificial intelligence applications is not an abrupt process but a gradual one. If you look at the business plans of some previous products, it's highly possible that the whole document didn't mention AI. However, as projects develop, people come to realize that what they're doing has AI applications as well,” Ji Yue said.
Currently, most investments in AI industry are in the business sector. Some predict that it will take another 5 to 10 years before AI could be applied in the consumer sector. But Ji Yue doesn't agree with that. "Toutiao is a perfect example of AI application in the consumer sector, and same for Guazi. Have you used NetEase Music? It also has AI elements, so you are enjoying the convenience brought by AI unknowingly. It's not the prediction of experts, but the efforts of entrepreneurs, that could bring artificial intelligence to the consumer sector. It will happen once you address the consumers' real needs.”
Two core elements: scenarios and data
When we take a closer look at the portfolio of Sequoia Capital China, we find that there are two kinds of companies in the AI industry. One type is pure AI companies like Yitu Tech, Mininglamp, 4Paradigm, Infervision; the others are companies with an enormous amount of data, like Toutiao, Didi and Meituan. What they have in common is that they not only improve their operating efficiency with artificial intelligence but also bring users brand-new experiences through AI.
The logic behind these investments, according to Ji Yue, is that people shouldn't focus too much on the technology part when making investment decisions in AI industry, but should concentrate on the use cases. It's still too early to create an AI application that could solve all the existing problems; this might not happen within the next 30 years. However, it would be much easier for AI to solve problems in a particular industry, like in healthcare, finance and personal security. Those AIs are "vertical AI" applications; by focusing on the vertical market, boundaries of problems get defined more precisely and therefore the technical difficulties encountered during data processing get reduced.
First and foremost: real use cases. AI that could solve specific problems.
Behind the investments made by Sequoia, there is one rule: the business plan for the AI application must be feasible. Lots of AI startups are holding a hammer and looking for nails. They do not know about traditional industries and are not aware of the pain point in those industries. Whether or not those nails exist is the problem people holding the hammers have to think about carefully.
So, is it necessary for the founding members of AI startups to have industry background? How important is technology in AI startups, compared with a deep insight of the pain points in the industry? According to Ji Yue, a background in the vertical market is not necessary; an understanding of the needs of users is much more important. Take Mobike as an example. Its founder, Hu Weiwei, was not in the bike industry herself. What she did was to find out the real needs, and then realize what value AI had in addressing them.
China's AI in a Macro Perspective
China is experiencing a late-comer advantage in the AI industry. The application of big data is emerging in multiple industries; people have already realized the value of big data, while at the same time artificial intelligence is mature enough to be commercialized. Therefore, big data, cloud computing, artificial intelligence and SaaS are getting combined together in China, creating tons of start-up opportunities. Meanwhile, Ji Yue also reminds the founders not to apply those concepts mechanically. Whether or not a business model could succeed is based on reasonable use cases; customers are willing to pay when your product or service could bring values to them. The users of Toutiao don't care if AI technologies have been running behind the application. They only care about seeing what they want to see, and that's enough.
Companies also must incorporate big data into the practice of AI, since AI produces the best possible results when the algorithms are trained with large datasets.
Take DiDi Chuxing as an example. Data shows that DiDi had already reached 1.43 billion of ride requests annually as early as in 2015, making it the second largest number of daily transactions worldwide (only TaoBao has more). Currently, DiDi is accepting over 20 million ride requests each day, with more than 30,000 requests per minute from users during rush hours. Didi is now beginning to predict users' destinations using AI.
Another example would be Mobike. At this moment, Mobike has over 100 million registered users, with 20 million ride requests daily. It is the largest online traveling platform worldwide per number of requests. In just July this year, Mobike's mobile app has hosted 648 million client sessions and 46.8 million hours of client session time.
Currently, all Mobike's bicycles are equipped with IoT communication chips and satellite navigation chips, which are compatible with major satellite navigation systems worldwide such as China's BeiDou, United States' GPS and Russia's GLONASS. These chips are producing 20TB memory of traveling data on daily basis, upon which Mobike is able to make forecasts of supply and demand for rentals, provide guidance for operation and deploy geo-fencing to address illegal parking incidents with the assistance of Mobike's own AI data monitoring platform “Magic Cube”.
AI's Talent Gap
It is possible that, in the foreseeable future, to be a successful company in any industry you'll have to use AI. With this assumption, there would be a huge gap in the supply of AI talents. It is the why Andrew Ng founded Deeplearning.ai and 4paradigm group founded 4paradigm university.
“Acquisition of talent is a challenge for any startup, but especially for those in a new industry. Every AI company right now is faced with the scarcity of high end talent. Therefore, it requires the CEOs of these startups to have strong technical background, so that they can locate and hire suitable people.”
Indeed, other than the acquisition of talents, the founders of startups would also have a series of problems to consider: sales, management, operation, and the coherence between product and client's needs. But the major issue lies in the founders themselves - it is entirely different to manage a company with 10 people than one with 200, and founders must make quick adaptations, and maintain a grasp over an an ever-changing field.
According to Ji Yue, while all the merits from a successful startup should be credited to the entrepreneurs, what the investor can do is to provide the CEOs with advice on strategy, financing, acquisition of talents, and operation, based on the combination of his or her network and resources, as well as their own experience.
A promising industry necessarily attracts the entry of large amounts of capital. As for the investors, the target eventually comes to the top 10 percent of the companies within the industry. “It is always the case that less than 10 percent of the companies generate more than 90 percent of values, whereas 5 percent of the companies produce 95 percent of return in TMT industry, a phenomenon which remains constant. Therefore, Sequoia doesn't care about whether or not there's a bubble in the industry, or whether the average valuation in the industry is high or low.” Ji Yue said. Sequoia is always looking for that 5 percent.
Sequoia has always been the fund that makes major investments in the "A" round; it is the DNA of Sequoia. Now, Sequoia also begins to pay more attention to earlier pre-"A" round investments. Ji Yue says, “Sequoia now actively starts earlier pre-'A' round investments. We welcome ambitious entrepreneur come to Sequoia at pre-'A' or 'A' round at anytime to gain best resources and race together for the long haul.”
红杉中国的 AI Map
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