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At the end of domestic AI is the database

At the end of domestic AI is the database 2024/06/27 08:40

Text: Poetry and the starry sky

ID:SingingUnderStars  

Recently, I got the internal test permission of the Kuaishou AI video model Keling, and I have made a lot of attempts, especially after opening the picture video, the usable value of Keling is very high.

At the same time, Sora, which was released in February, is still drawing PPT. In the field of open source large models, Alibaba's Tongyi Qianwen 2.0 has taken the top spot in the world.

Judging from the practical application in the past few months, AI technology really has no moat. As strong as OpenAI, the first-mover advantage is getting weaker and weaker.

Apple claimed at the press conference that it would integrate multiple AI tools such as chatgpt, and China may cooperate with Wenxin Yiyan. Some netizens are worried that there will be a difference in experience when switching to domestic AI.

However, Xingkong Jun carefully studied Apple's AI function and found that it is nothing more than automatic extraction of information from ID pictures (SF Express has already achieved it), automatic summary of email summaries (DingTalk meeting summary has been used), automatic audio transcription of text and semantic summary (DingTalk, Tencent Meeting, iFLYTEK said: That's it), AI-generated emojis (Rotten Street), etc.

Players like Xingkongjun, who use AI with high intensity, can responsibly tell everyone that the vast majority of domestic AI can do it or even do it better.

Compared with last year's frequent use of ladders to access Chatgpt、ClaudAI,This year, you basically only need to use domestic Kimi、Tongyi Qianwen、ChtGLM is enough,In terms of research report analysis、Semantic summary, etc.,Domestic AI is basically the same as Chatgpt4 or even partially surpassed,Occasionally, the ladder is mainly used to access station C to download AI painting models。

Recently, two pieces of news have caught the attention of Starry Sky Jun:

First, Kai-Fu Lee's company announced that the company has successfully developed a new vector database "Descartes" based on full navigation graphs, and has won the first place in the evaluation of 6 datasets on the authoritative list ANN-Benchmarks.

The second is OpenAI's announcement of the acquisition of database analytics company Rockset. Coincidentally, Rockset is also working on vector databases.

The so-called vector database is a vectorization of text, speech, images, videos, etc. Vector databases can handle more unstructured data (such as images and audio) than traditional databases. In machine learning and deep learning, data is often represented in the form of vectors.

Compared with traditional database applications, AI stores mainly unstructured data, so vector databases are more suitable.

In terms of domestic databases, Tencent has just released a cloud-native vector database, and GBase has also released a vector database.

With the development of AI technology, databases have also ushered in a new era of blooming. Traditional databases such as Oracle are gradually retiring from the stage of history.

01

Dameng Data was listed on the Science and Technology Innovation Board

Nowadays, many young developers think that domestic databases such as Dameng and Jincang are nothing more than modifications and encapsulations on the basis of open-source databases, so they can directly adapt to the components of databases such as Oracle.

Poetry and the starry sky, the end of domestic AI, is the database

In essence, it is still the same sentence: as soon as it is open source abroad, it will be self-developed in China.

What they don't know, however, is that the earliest version of Dameng Database, CRDS, came out in 1988, when MySQL didn't even exist.

 During the Sino-Japanese friendship period, Japan supported China's Wuhan Iron and Steel construction.

In 1978, Japanese technicians installed equipment in the hot rolling workshop of Wuhan Iron and Steel Co., Ltd., and before evacuating, they destroyed all technical data, including database software, which amounted to 3 truckloads. At that time, a young assistant teacher from the Computer Department of Huazhong Institute of Technology happened to study in Wuhan Iron and Steel, and when he saw this scene, his heart was shocked.

Since then, the young man has been determined to develop a database that he can take into his own hands.

He is the founder of Dameng Data, Feng Yucai, and when Dameng Data was listed, he was 80 years old.

According to the Dameng data prospectus, the company serves well-known users including China Construction Bank, Bank of Communications, China Everbright Bank, Industrial Bank, Guangfa Bank, China Development Bank, Chinese Life Bank, Postal Savings Bank, Chinese People's Insurance, State Grid, TravelSky, China Mobile, China Tobacco, State Administration for Market Regulation, People's Procuratorates at all levels, People's Courts at all levels, National Development and Reform Commission, National Immigration Bureau, Securities Regulatory Commission, Shanghai Stock Exchange, Shenzhen Stock Exchange, etc., and has been successfully applied to dozens of fields such as finance, energy, aviation, communications, and party and government organs. According to a report released by CCID Consulting and IDC, the market share of the company's products from 2019 to 2023 ranks among the top domestic database manufacturers in China's database management system market.

It can be seen that the database of China's core lifeblood industry is now firmly in its own hands.

However, according to Xingkong Jun's understanding, the market share of very good domestic databases such as Oceabase and TiDB is also very high, and the current domestic database is in the stage of a hundred flowers.

Combined with the current wave of domestic substitution, it can be inferred almost brainlessly that the market space of Dameng will further explode.

02

How turbulent the autonomous and controllable track is

Xingkong Jun often said to his friends that life is a wilderness, don't stick to plans, plans, assumptions, etc.

In the field of investment, the track of independent and controllable is the boundless wilderness.

Five years ago, Xingkong Jun advocated the new energy vehicle track; Five years later, Starry Sky Jun began to advocate an autonomous and controllable track.

With the promotion of platforms and application policies such as big data exchanges and data asset entry tables, China has embarked on an unprecedented path to digital economy.

And the foundation of this road is autonomous and controllable. The database of the railway system has been changed from Sybase to self-developed, and the database of two barrels of oil has been changed from Oracle and Myssql to Oceanbase, Jincang, Dameng...

In order to make security assessment more convenient, private enterprises have also begun to gradually migrate to domestic systems, thus gradually driving the whole industry to use domestic independent and controllable systems.

According to the prospectus, Dameng's performance has been full of twists and turns, and after reaching its "peak" in 2021, it will decline in 2022.

Poetry and the starry sky, the end of domestic AI, is the database

Source: Straight Flush iFind Cartography: Poetry and the Starry Sky

The main reason is that in 2021, a wave of localization substitution will be carried out in central enterprises and agencies. Because of the large base, there will be a decline in 2022, but based on the company's own advantages, the performance in 2023 will re-enter the growth channel.

03

AI will reshape all traditional businesses

Although Xingkong Jun does not believe that there is any threshold for AI, the application of AI will bring revolutionary changes, that is, AI will reconstruct all traditional businesses. The process of restructuring is a huge opportunity for enterprises and investors.

For example, the AI transformation of a traditional information system that Xingkong Jun participated in replaces the steps of manual copying document entry system with AI+RPA (domestic ChatGLM for the base, ready to switch to Qwen2.0 in the later stage).

The database industry will also encounter such changes, and AI can turn the manual operation of traditional databases into automatic operations.

In the face of large-scale data and different application scenarios, traditional database components have problems such as insensitive business types and weak query optimization capabilities. At present, there are studies to replace traditional database components with machine learning algorithms to achieve higher query and storage efficiency and automate various tasks, such as automatic management of computing and storage resources, automatic prevention of malicious access and attacks, and proactive intelligent database tuning. Machine learning algorithms can analyze large amounts of data records, flag outliers and patterns, help organizations improve security against intruders, and perform patching, tuning, backup, and upgrade operations automatically, continuously, and without human intervention while the system is running, minimizing human error or malicious behavior and ensuring that the database runs efficiently and securely.

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