There are more FAs looking for AI projects than projects

Wen 丨 Zhang Xue

Editor丨Zhang Lijuan

Source丨TouZhong.com

In the past week or two, under the frequency of AI technology updates in "days" and the transmission of celebrity effects, some interesting phenomena are also happening in the investment circle. For example, more and more FAs are flocking to AI on the market, all of which are more than the number of projects. "Project" here refers to entrepreneurial projects that really have a team.

When chatting with Yang Sihua (pseudonym), an FA practitioner in the software industry, she told me: "Now there are fewer and fewer investors looking at software, the situation is stronger than people, now they are coming to them to ask for AI projects, the market has been cold for two years, there is no way, I can only turn to AI first." ”

She also said: "In addition to FAs like them who used to look at software and understand AI to join the tide of project grabbing, there are also those who have seen new energy and new materials before and also come to AI." ”

FA on the air vent

Although I admit that AI is hot this year, I am still a little surprised by the addition of people in the new energy industry.

Seeing that I was puzzled, Yang Sihua explained: "Although new energy is very popular, but the project is not easy to find, on the one hand, there is no shortage of FA for high-quality projects, on the other hand, there are more RMB funds that invest in new energy, and the inspection period is relatively long, but it is not as cost-effective as the current AI projects." ”

There is another detail that can be supported by the enthusiasm of FAs to join the AI wave - that is, their circle of friends.

It is reported that they have recently shared AI news and research reports, and some people will go to various occasions and platforms to express their views on AI. In this regard, some people ridiculed: maybe in the same period last year, he was still forwarding some research on new energy and expressing his views, and now he wants to prove that he is really a person in the AI industry in this way.

Another interesting phenomenon is their enthusiasm for learning AI at Station B.

Here I have to mention the former Amazon chief scientist Li Mu, he is an AI bull, and at the same time long-term on the B station to do some AI paper intensive reading video, in order to make up for AI knowledge as soon as possible, many people in the investment circle go to Li Mu to learn, and some people say: "I learn from Li Mu", in the industry, this is very funny. However, to some extent, it also reflects the anxiety of FA catching up.

But even so, many new FAs still can't see any decent AI projects, especially particularly popular projects, and they can't meet at all. For example, the most difficult appointments on the market at present are projects from Microsoft Asian Research Institute, Chinese Academy of Sciences and Tsinghua Department.

The reason behind this is that the project team does not want to become a teacher to teach a bunch of students. What the founders want most is to meet one and pay the next day. Instead of chatting about 100, 80 of which do not understand, they all need to be taught, the other 20 have 10 and a half understand, and in the end only 10 have really seen it, and only one or two have a deal, such a transformation is too tiring.

Many FAs will say that they have been paying attention to AI for a long time, but when talking to the project team about some technologies, they can't talk, and even there will be a large period of silence, because the founder of this field is generally a scientist type, in order to make everyone understand, he will often convert scientific language into a common language, but some FAs and investors still can't understand.

So at the very beginning, the founders will directly delete those who pretend to be watching AI, resulting in many institutions not being able to talk about the project.

In this way, it has also led to a divergence on the FA side. For example, some FAs who are deeply engaged in the AI industry even have the confidence not to contact new projects this year and continue to serve old customers, because in their opinion, Xinla's team and project uncertainties are too many, and it will take at least a year or two to really see the doorway. They will also complain that hot projects in the market abound, such as those that do collaborative office, collaborative design, and intelligent customer service.

"Mixed with fish and dragons"

The madness of FA has also made the entrepreneurial projects in the market mixed.

"Now that there are projects everywhere, it is not even too much to describe as an information explosion, and I feel that diligent investors can see 10 AIGC projects a week. Most of the projects are still early, and some founders are still in big factories or schools. Wang Mengfei of the small dinner table said.

In addition to some entrepreneurs who see the opportunity to take the initiative, investors and FAs are now fooling all kinds of people to start businesses. Including master's students, doctoral students and some high P of large factories, the whole market is in a mixed state.

Wang Mengfei believes: "The current status of the AI industry is a bit like the feeling of the mobile Internet in 2014~2015, the industry is facing a new generation of technological revolution, all applications will be reconstructed by AI, but where will there be huge opportunities, which are bubbles, we need to identify each other." ”

According to another FA Li Xinyan (pseudonym), the highest enthusiasm for entrepreneurship is now in universities, because this technological change first set off a wave in the academic community, and at the same time, with various policy support, joining the AI wave has become a consensus.

It is worth mentioning that in the first wave of AI entrepreneurship, it was these scientists and high-caliber students who were the first to end and were popular with capital, such as Yin Qi and Tang Wenbin, who graduated from Tsinghua's Yao class, Tang Xiaoou, a professor at CUHK, and Zhou Xi, who gave up his status as an expert of the Chinese Academy of Sciences. Now that AI 2.0 is coming again, many people still want to copy their entrepreneurial dreams.

For large factories and high P, coming out to start a business has become the choice of more and more people, but in the first two years, due to the impact of the macro environment and the influence of wind rotation, the space for them is very limited, and AI as the standard of technical capabilities of large factories, for them, is also the ability to come hand-to-hand, we also see that many newly formed teams this year are recruiting senior product managers, which also makes many high P eager to try.

In addition, the crazy valuation of AI projects in the primary market has also given these entrepreneurs confidence.

"Last year, many AI companies were in a very difficult situation, their expectations for financing were very low, and this year there has been a huge change in attitude, when pushing projects, some institutions have shown strong interest as soon as they hear that they are technology bosses, the team is also very solid, and they have done a lot of accumulation, and the valuation of the projects we have contacted has generally increased by two or three times." Li Xinyan said.

Of course, there are also valuations in the industry that have risen very exaggeratedly. Some have doubled from several million dollars to tens of millions of dollars, and some have a valuation of only $500 million in the middle of last year, and rose to $1.1 billion at the beginning of this year, and the industry still gives positive signals in terms of valuation.

In terms of business model, there are currently more API calls and private deployment. Although many people now want to say that they want to make a big model, in fact, Open AI only does the most difficult thing, but it is not necessarily the most profitable link, the focus is on the creation of ecology.

A game of big wins and big losses

In fact, whether it is an FA that changes course with the trend or a scientist who forms a group of entrepreneurs, the essential driving factor behind it is capital.

Money comes, everything comes. What prematurely promoted this entrepreneurial wave to the level of capital competition is that some bigwigs have recently announced their entry into the game one after another.

For the addition of the big guys, some people think that this is a double-edged sword. On the one hand, they have increased the popularity of the entire track, and to some extent, they have given investors a lot of confidence. On the other hand, they prematurely pushed industry competition into capital competition, and for many other early projects, they are now passive.

AI entrepreneurship is different from other industries, it naturally has a higher demand for capital, because it is indeed a direction that does not get enough money and does not even have the opportunity to get on the table. In this way, once the project has an idea, it will inevitably have some contact with the capital circle. We can see that until now, most of the previous generation of AI companies were still in a loss-making state.

On the surface, now in the VC circle, everyone is looking at projects and looking for projects, but the whole track is still very cold.

Although many funds say that they want all in AGI (general artificial intelligence), when asked what they want to invest in, the boss does not have a conclusion. Accordingly, what should I vote for? How to vote? How to expect the return on investment, nine out of ten investors are confused.

Of course, many funds that choose all in AGI this year, there are more dollar funds, firstly, the dollar fund has experienced the silence of the capital market last year, the pressure of investment is great, and secondly, there is a new theme, and this wave of momentum mainly comes from overseas, so the sensitivity and enthusiasm of the dollar fund are higher.

It is understood that at present, many RMB funds are also paying attention to the situation of the AI industry, but now the stage of many projects is too early, whether it is products, applications or commercialization paths have not taken shape, and the asking price is not cheap, so it is difficult for RMB funds to shoot.

For the prediction of the future market, investors have also given a relatively consistent judgment, that is, the investment and financing transaction volume in these segments will not be particularly high. Because the really valuable companies in this track are relatively scarce, as far as the team is concerned, there are very few people in China who can really do AI and make big models, among them, there are very few who are willing to come out to be a company and have very clear business ideas.

"Actually, the real deal is still very small, and the market is very cruel. Although there is no shortage of speculators on the track, it may be screened out very early without outstanding competitiveness, including products, technologies and complementary founding teams. Wang Mengfei said.

In the long run, the trading volume of this track is still more active in the early days, like the angel round, it has nothing to verify, and the financing will be smoother. But once it comes to the A round and B round growth stage, there are not many projects that can really run PMF.

Finally, when talking about the portrait of high-quality projects in the wave of AI 2.0 entrepreneurship, I got this answer: on the one hand, we need a strong enough operation and management team to make the internal development context and path clear enough, on the other hand, we need a strong scientific research team to ensure the density of talents, and third, in AI training, whether it is data or hardware purchase, it requires a lot of financial barriers.

Under such a portrait, some people are completely pessimistic about the current domestic entrepreneurial situation, in their opinion, it is very difficult to succeed in the AGI industry, before the ChatGPT fire, this is a very unpopular track, if you use the general analysis framework of artificial intelligence, including data, computing power and algorithms, and each of these three links is difficult.

Again, this is why everyone is cautious, because this is a "pinching" investment, institutions want to be able to shop around to see who can run out, after all, once the wrong team is selected, the future is largely unprofitable.

In Li Xinyan's view, "especially the entrepreneurial battle on the big model is very cruel, and it is very likely to be a big win and a big loss." ”

(At the request of interviewees, Yang Sihua and Li Xinyan are pseudonyms in the article)