Bleeding, hemostasis, and recreation of hematopoiesis, when will AI unicorn nirvana nirvana?

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This year, Galing's deep pupils and Yun successfully listed on the Shanghai Exchange from Technology have added a lot of lively to the AI ​​industry. A "star" aura since its establishment, and a background of the "national team". How do you think these two are seed players who cannot be underestimated in the AI ​​industry.

However, this time the ideal and reality transformed too fast. On the first day of the listing of Guling's pupils, the stock price was broken, and the trend was not optimistic; Yun became the focus of market doubts from the ability to burn money in the prospectus.

But in fact, this kind of situation has been weird. There are more or less similar problems in other AI manufacturers such as Shang Tang and Yitu. Moreover, it is not difficult to find the development of other manufacturers. The current situation of deep pupils and clouds is the epitome of the domestic AI unicorn listing, and the true portrayal of the overall development of the industry.

Blooding becomes inertia

For a long time, AI companies have become the norm, and most AI companies seem to be carrying unspeakable funding pressure. This may also be why more and more AI unicorn in recent years is more attached to the market. Objectively speaking, these AI companies are basically making money and not making money. Even listing does not mean once for all.

The fact is true, so I have been successfully listed on the market, Shangtang, Shang Tang, and Yun. The financial report has always showed that in the first half of 2022, the losing loss during the Galian deep pupils was 12.5616 million yuan; Losses from 325 million yuan during the period.

The problem of profitability is still a dark cloud floating on the heads of AI companies.

面对这样的现状，AI独角兽们好像都已统一口径，表示目前正处于“战略性亏损”阶段，即为了长期收益而做出现实牺牲，在前期亏损的情况下也持续投入，以求Large -scale commercialization in the future. In other words, AI's current loss status is the active choice they make in order to achieve future sustainable returns.

At this stage, the implementation of losses at this stage is often continuously raised in specific operations. As we all know, AI companies are technical and talent -intensive enterprises, and most of the focus of capital expenditure is biased towards technology and talent.

Over the time, artificial intelligence products are technology -driven products. In order to ensure the implementation of technology from conceptual to the "safety" of products, not only the early research and development investment is high, but the late iteration update speed must be kept up. Operation guarantee. It can be said that technology research and development is the core of artificial intelligence enterprises. At present, the expenditure in this area seems to be logical.

From the perspective of the financial reports in the first half of this year, after Shang Tang deducts the shares -based salary expenditure, R & D investment is still as high as 1.88 billion yuan, which is 133.1%of the total income; The investment was 57.101 million yuan, accounting for 48.73%of operating income.

Secondly, compared with other industries, AI companies have more demanding requirements for the knowledge background of employees. Correspondingly, they are relatively high in terms of talent costs. Among them, the typical equity incentive system of AI companies is a large amount of expenses. For example, the share payment fees confirmed by Yun from Technology from 2019-2021 are 231 million yuan, 190 million yuan, and 177 million yuan, respectively; Galing deep pupils are expected to have a total share payment fee of 1.441459 million yuan from 2021-2024.

The scale of income is not large, but the initial R & D investment and high share payment costs, the speed of spending money is greater than the speed of making money, which is the common problem that causes most of the current losses of AI companies.

From the current development path of major AI companies, it is not difficult to see that their profit logic has formed a common idea -first bleeding to go public, and then pursue continuous growth and improvement of profitability. However, the AI ​​unicorn has completed the first step of "listing". At present, it is unknown that the continuity is still in the pursuit of growth. Blooding is still continuing. It is still a relatively difficult thing to get rid of the problem in the short term.

Objectiveness is imminent

In common, the long -term "bleeding" of enterprises is not conducive to its sustainable development. Moreover, the current market situation is changing, and the hemostasis of AI manufacturers is even more urgent.

On the one hand, capital is not patient, and the secondary market is not high to the tolerance of this large -scale loss. The AI ​​air outlet is landing, and the industry is in the stage of removing and squeezing water. Now it is obviously not when the concept of hype was allowed to pay for investors. If AI companies still cannot eliminate the risk of continuous expansion of losses and make investors see the dawn of profit, I am afraid it is difficult to appease investors' negative emotions to the AI ​​market.

On the other hand, players such as Shangtang and Yuncong are mostly based on G -end customers. The right to speak is mainly controlled by terminal customers. As service providers, they are relatively lacking of the initiative of repayment. In addition, under the epidemic, the development of downstream B -side enterprises will be more or less affected, and the recovery of the withdrawal may be slow. From the perspective, AI companies' own cash flow is not stable.

In view of this, AI players have also gradually implemented targeted solutions about "hemostasis". According to the previous, the crux of excessive bleeding from the AI ​​manufacturers is mainly because the scale of revenue does not keep up with high R & D costs, and its "symptom" is to start from improving research and development efficiency to minimize R & D costs.

In this regard, AI players are converging in pace. In the past, Shang Tang created a new intelligent infrastructure -Sensecore to enhance AI computing power and achieve large -scale mass production of commercial models. Later, there are Guling deep pupils upgraded the artificial intelligence algorithm platform to reduce artificial intervention and achieve the purpose of rapid delivery of models. It is worth mentioning that cost management is related to the ability of enterprises to resist internal and external pressure. For AI factories that are currently expected to continue to reinvigorate technology in the future, it is particularly important to have cost management capabilities. For example, Gelling's deep pupils have calculated that when gross profit can cover cost costs in the future, it can achieve a profit of turning losses in 2023. It can be seen that the key role of cost control on its profit is very obvious.

It is undeniable that the current AI manufacturers are indeed good in cost control. However, in terms of the current facts, the research and development costs of each family are still in a high level, and the hemostatic effect needs to be strengthened.

Bleeding needs to be verified

It is said that the first -level market is looking at the story, and the secondary market depends on strength. At present, AI technology is widely landed. If many players cannot find more realistic value of AI outside the story, I am afraid that they will gradually lose their meaning. It is more optimistic that many AI companies are now thinking about changing, looking for more feasible commercial scenarios.

First, expand the scope of business.

As we all know, AI companies such as Shangtang, Yuncong, Guling deep pupils generally have the problem of high customer concentration, and it should be explained that the disadvantages of this business status are still relatively significant.

First of all, it will cause a poor anti -risk ability of AI companies, because once a single customer with a large sales volume has risks or changes, it will adversely affect the overall performance of AI. Secondly, the high concentration of customers is not conducive to AI companies to cultivate their own bargaining ability, and it also hinders some obstacles to the realization of subsequent profit targets.

From this point of view, in the future, if these AI companies want to achieve the purpose of sustainable returns, they will continue to expand new areas to reducing the dependence of major customers. It is worth mentioning that in recent years, major AI factories have begun to carry out multi -dimensional layout to expand more business types and have wider scope coverage.

For example, in terms of application scenarios, Guling's pupils have carried out forward -looking business layout in the two new areas of sports health, rail transit and transportation; in the algorithm, Shang Tang continued to develop its own research on vision, natural language processing, and voice recognition. Algorithm development expands the existing business scope based on the original visual processing.

Second, break through market limitations.

Most of the AI ​​companies are basically the business of to g and to B. The revenue is greatly affected by a small number of large orders, and the profitability situation is relatively passive. The most important thing is that with the gradually appearing in the homogeneity of various products and the addition of more giants, the difficulty of this revenue model in the future may also increase. The AI ​​unicorn seemed to realize that such problems were, and they began to test the development of the TO C field.

In August 2022, Shangtang released a hardware product for the consumer -level market- "Yuan Radish" chess robot. In September of the same year, Galing deep pupils launched a self -developed immersive human -machine interaction system Metasense and big scene immersed interactive interaction game. The idea of ​​the two is also obvious, that is, I hope to explore the transformation of corporate products and business models by serving C -side users.

However, compared to the players who have been layout on the C -side layout early on Baidu and HKUST Xunfei, the steering of Shang Tang and Ge Ling's deep pupils is not fast, and the current turning of the three families of the cloud, Yi Tu, and Kuangjie Viewing the current steering of the three households currently turns. The action is not large. Under the strong enemies, whether you can cultivate the B -end and G -terminals all the year round, the four dragons of AI can quickly advance in the C -end, and it remains time to verify that improving the right to speak.

In addition, there are many factors for commercialization of these new business scenarios, such as insufficient delivery capabilities, low acceptance of customers, or the ultimate commercialization benefits of the customer, or the final investment in the early stage. Therefore, AI companies with limited funds will be more cautious in Takura's planning.

After all, unlike fast iterative consumer products, for AI companies that have invested high research and development, the risk of R & D and commercial use of hard technologies such as AI. Once failed, the high costs they invested will be paid to the east. In short, it is unknown whether the development of new areas is bold and adventurous. It is unknown whether it can help the profit targets of A unicorn.

Competitive environment upgrade

The current industry has returned to rationality. The AI ​​manufacturers must improve the hemostatic system and enhance self -hematopoietic ability. Essence

According to data from the China Communications Institute, the scale of the domestic AI core industry in 2022 is 157.3 billion yuan, with a compound growth rate of 58%. The continuous and rapid growth of the industry means that more AI companies may benefit from it. At the same time, the rapid development of the track will also make the competitive relationship between players become more tense.

In the case of, hardware manufacturers represented by Hikvision are also seeking intelligent transformation and supplementing shortcomings in software. Its products have covered multiple fields such as smart homes and smart medical care. Secondly, many Internet giants such as Ali and Tencent have also begun to accelerate the layout of AI tracks and compete with other AI companies in the industrial Internet field.

These players or hardware have outstanding strengths, or have strong funding forces, the competitive pressures to be faced by Ge Ling deep pupils and AI Four Little Dragons are undoubtedly huge.How to maintain its own advantages next is to achieve long -term development or the key issue that these AI companies need to focus on.As for the solution of the problem, it can be started from two aspects.First, take into account innovation.Pay attention to the realization of product and solution innovation, and combine other advanced technologies such as big data to integrate and innovate to meet the diversified needs of various industries and users for artificial intelligence products.Second, maintain stable operation.Expansion carefully and focus on maintaining the health of cash flow.

In summary, most AI companies are still in a state of blood loss, the ability to make hematopoietic has not yet been consolidated, the capital market's expectations for their expectations are not high, the competition in the industry has intensified, and the survival situation of each AI company is not optimistic.Therefore, whether it is a long pupil or AI four dragons, there is still a long way to go to the goal of waiting for the income and stable development, and the listing is not the end.

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