The fourth paradigm sprint ipo, is hard to escape AI players?

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In the past two years, the artificial intelligence track needs to be reflected in two years. On the one hand, under the losses, the financing difficulty of celebrities AI companies has increased. Yuncong and Shang Tang, either to go public, or have a decline in the stock price, and the voices of unsightly capital markets are here one after another.

On the other hand, the commercial application of artificial intelligence did not see more surprises, and even breeds some unreasonable products and chaos in the fields of medical care, creation, education, and caused the public's questioning and discussion of AI.

Faced with artificial intelligence, the problems raised by the outside world are no longer idealized, but more and more realistic. When AI burn money so much, when can I make money? As an ordinary consumer, it seems that you have not yet felt a good life brought by AI? The value of AI really has cloud computing and 5G?

Especially in terms of commercialization, when tens of billions of investment can be recovered in the early stage, AI companies and investors behind them are quite concerned. After all, many AI founding companies that have been highly hoped have not seen the dawn of profit, but instead still for it, but they are still for it. The track poured a pot of cold water.

Nevertheless, the hard -headed listing industry has become the fate of AI startups. After the Cambrian, Shang Tang, Viewing, and Clouds, the fourth paradigm also began to sprint the IPO.

Decisions AI breakout

Different from Shang Tang, Yun Cong, and Viewing, the fourth paradigm goes to the development direction of decision -making AI. What is decision -making AI is simply helping companies carry out AI technology or solutions to operate, manage, and produce, which is essentially similar to enterprises integrating SaaS services.

The prospectus shows that the core product "prophet platform" and the service scenario of solutions are mainly focused on the three aspects of sales and marketing, risk management, and operating efficiency. Enterprises make decisions.

Comparing the cloud, the fourth -style product form is based on IaaS as the computing power basis to provide enterprises with PaaS and SaaS services. It can be said that the fourth paradigm is a comprehensive AI solution provider.

Most of the Shangtangs followed the product AI route. The fourth paradigm decision -making AI is mainly concentrated in two points. First, the decision -making AI is mainly to b or to g, and the product AI is more to c or to b (g) to C. It is to allow the product to meet the needs of consumers and bring a better experience to the public.

According to the prospectus, there are dozens of industries in the fourth paradigm, including finance, energy, transportation, retail, medical care, manufacturing, etc.

Theoretically, the imagination of decision -making AI is very high, and it is a rigid need for all enterprises to intelligently upgrade. The reason is that decision -making AI is not only a business tool, but also a strategic tool. Today we talk about cloud computing. It is more about the need for digital upgrades and need information technology in the middle Taiwan. However, it is easy to ignore the strategic digital needs of the enterprise. Decision AI can just solve such demand.

From the perspective of revenue growth, decision -making AI is entering the stage of fast commercialization. The fourth paradigm shows that from 2019 to 2021, revenue was 460 million, 940 million, and 2.02 billion, respectively, significantly expanded.

From the perspective of industries, the demand for decision -making AI in energy power, telecommunications, transportation and other industries has continued to expand. According to the prospectus, among the fourth paradigm in 2021, among the revenue of the fourth paradigm, the energy power, telecommunications, and manufacturing industries increased by 7.2 percentage points, 0.9 percentage points, and 2.6 percentage points year -on -year respectively.

In addition to the mainstream scenarios such as the early large -scale commercialization applications such as retail and finance, the fourth paradigm is opening the situation in more scale and heavy asset industries, indicating that the application potential of AI is considerable.

Can't get rid of a common problem

Although the decision -making AI breakthroughs occupy a world of the track, the fourth paradigm is still artificial intelligence players after all. Regardless of the monetization model or business progress, they are similar to Shang Tang and Yun Congs. Therefore, the fourth paradigm is also difficult to escape the development of AI players.

The loss of losses that are difficult to reverse are the first common problems that cannot be escaped by the fourth paradigm. Earlier, when Shang Tang and Yun Cong disclosed financial data for the first time, public opinion storms were caused by a lot of losses.

The prospectus shows that the adjustment of the fourth paradigm 2022H1 is 220 million, a narrowing of 12%year -on -year. In the past three years (2019 to 2021), the adjustment of the fourth paradigm has a loss of 320 million, 390 million, and 570 million, respectively.

The reason for the loss of the fourth paradigm is the same as other AI players. The cost is too high, and the gross profit is difficult to cover. However, objectively speaking, AI companies are too normal. In the early stages of commercialization, the two costs of technology and marketing are unavoidable. If these AI companies actually have a scary "high gross profit", the software part can even reach 90% The above, but AI companies are technology -driven enterprises. In the middle and late stages of commercialization, they may not need marketing, but the investment in R & D needs to be unswerving.

At present, the financial performance of the fourth paradigm has signs of improvement. The main expenses of 2022H1 have declined, but whether it can achieve a loss or step into a steady profit stage in the future. On the one hand, it depends on the growth rate of income. Look at cost optimization.

The sustainability of the realization is the second common problem that cannot escape the fourth paradigm. The monetization here continues, not whether it can find new customers, but the new income brought by old customers, which can be understood as customer income retain.

From the perspective of the prospectus, the peak income peak contributed to the fourth paradigm was in the first year, that is, the early stage of cooperation, and the income level that could be contributed since then was relatively low. For example, in 2019, the number of customers A and the fourth paradigm trading was 94.449 million, accounting for 20.9%. No client A was seen in the first five rankings in 2020 and 2021. There may be two reasons. First, the business model of the fourth paradigm contains the software license model. The purchase of users is equivalent to one -time buying. The subsequent payment standards are based on the additional computing power scale and no longer need to pay for software. Second, users have purchased all the fourth paradigm. Products and services, subsequent payments based on additional computing power are not large.

This also means that the first delivery of new customers or new products can drive a significant increase in the fourth paradigm revenue. This is not difficult to understand why the fourth paradigm has accelerated to more industries such as transportation and medical treatment, and even uses capital mergers and purchasing vertical industry players to accelerate market share.

Passive follow -up industry

Under the epidemic, AI and cloud services have been disadvantaged by both. One is that on -site deployment business cannot be carried out or has great resistance, and the other is that many subjects' contracted industries or industrial demand is weak.

Alibaba Cloud, Tencent Cloud's extension of the communication and power industry extension, and Shangtang's strengthening of the business layout of the new energy vehicle industry, all of which are adjusted to deal with industrial fluctuations. It can be said that under the current circumstances, digital intelligent service providers can only passively follow the industries with expansion effects.

The fourth paradigm currently focuses on the demand for decision -making AI products and services in energy power, medical care, transportation and other industries. On the one hand, some industries are in a state of weak demand due to epidemic conditions and other factors. The prospectus shows that 2022H1, the fourth paradigm comes from the revenue of the financial and media industries decreased by 20%and 63%year -on -year, respectively.

On the other hand, energy power, medical care, transportation, manufacturing and other industries are in digital transformation and prosperity, and they are more popular at the financing level. According to the prospectus, 2022H1, the fourth paradigm comes from the revenue of the energy power and telecommunications industry by 35%and 100%year -on -year, respectively.

In addition, from the perspective of customer unit price, the energy power and other industries can bring a higher net worth transaction net value to the fourth paradigm due to business scale and complexity. For example, in 2021, the transaction volume generated by the energy power and retail industry with the highest contribution to the fourth paradigm was 130 million and 33.29 million.

For the fourth paradigm, the advantages and disadvantages of passive followers are clear. The advantage is that the fourth paradigm can enjoy the technological upgrade dividends of the expansion industry, build a benchmark customers faster, form a brand radiation effect on the entire industry, and reduce marketing and sales pressure.

However, the challenge is also obvious. The business model and demand of each industry are different. Entering and through new industries require more learning costs, technical costs, and channel costs. The fourth paradigm needs to continue to invest new industries in order Open the business boundary.

Application value is far more important than profitability

Today, everyone is criticizing the loss of AI companies. This is a business judgment. We should be more concerned about the application value of AI technology. If the application value is recognized or indeed brought about changes and subversion to the enterprise, the government or individual, then it Naturally, it will not be eliminated, and the profitability at the commercial level is also sooner or later.

In fact, from a cost perspective, AI players like the fourth paradigm are obvious to the value of the enterprise, which is to reduce the threshold. According to the estimation of burning consulted, the initial cost of the enterprise's self -built enterprise AI system is about 500 million, and the cost of operation and maintenance in the later period is about 50 million, and the annual cost of external mining is between 50 million and 100 million.

Regardless of decision -making AI or product AI, it still has considerable value potential in the future. First, the product and service level brings a sustainable and subversive experience, such as autonomous driving. Second, the development level of the enterprise forms a unique AI technology, coordinating the ecology, and making long -term feasible strategic decisions.

People and AI co -govern enterprises, society, and consumers and the public should be the existence of the long -term relatively ideal existence of artificial intelligence, and it is also the ultimate value of artificial intelligence in human society.

However, compared to this period, the current AI track is still in the stages of qualifying, tug -of -races, and knockouts. ; Second, how can my AI products guarantee the most important practical problems; third, whether my AI products really have general capabilities.

We should not overly worry about profitability, rush to AI's commercialization, maintain advantageous application scenarios, ensure appropriate input transformation efficiency, and allow customers to recognize technology. I believe that technology is the blood of the enterprise, which is the hard -core logic of AI players' long breakout.

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