At the beginning of this year, the phenomenon-level explosion of ChatGPT brought attention to OpenAI, the carrier of its underlying technology AIGC. With several buffs superimposed, the fate of the workers can be said to be ups and downs, and the fate is ill-fated. In China, the long-term value of AIGC has been gradually tapped, and people's office, entertainment and even lifestyle are being reconstructed. Enterprises hope to build applications that meet their own business needs with a low-code + AIGC model.
Have your cake and eat it too
Under the trend of digitalization, many enterprises want to use digital means to reduce costs and increase efficiency. However, "ease of use" and "customization" have always been incompatible. The advancement of AI has found a "medicine primer" for the "stubborn disease" that has stopped digitalization.
Gartner predicts that in the next five years at least 500 million new applications will need to be developed to meet the needs of enterprise transformation, of which 65% will be completed through low/zero code, and 75% of large enterprises will use at least four low-code development tools for applications development, and this percentage continues to increase.
Low code catches the fast bus of OpenAI
Behind the subversion, the direction is extremely important. The "AIGC + low-code" model focuses on combining AI capabilities with low-code platforms, raising the upper limit of platform applications and lowering the lower limit of platform applications.
AIGC+ low-code mode is an enterprise trying to hold the "steering wheel" of AIGC by itself. The principle of ChatGPT is to integrate a large amount of "data" such as text, pictures, and videos, and input them into the neural network of deep learning for learning and training for intelligent decision-making.
Based on AIGC's blessing, the delivery process can be transformed into an interactive language generation application, and complex requirements can be directly transformed into complex table structures, field types, association correspondence, process logic, and data indicators without the need for builders to use their brains. By describing the application in natural language, the application can be automatically built. The key application has data, processes, and can reach business personnel.
AIGC+ low-code, industrial digitalization heading for deep water
Among them, the generative low-code model needs to be trained on various data and processes. Through the integration, learning and training of "data" in different warehousing links of different industries, when the warehousing demand of a certain industry is raised, it can quickly Make smart decisions.
When more and more data are integrated, learned, and trained, the larger the amount of data, the more accurate the prediction will be. Careful friends will find that the path of AI building is not a general sense of "one-sentence generation application", but a role of "assisting in building robots".
The low-code track under AIGC is dark and turbulent
However, due to many factors, AIGC+ low-code has relatively large limitations, and still faces some problems from the perspective of the underlying technology. This is also the key to the fact that the current "AIGC + low code" cannot be "one step in place". The most obvious is that it cannot meet the business needs of very complex business logic.
For enterprises and developers, the cost of trial and error in technology is too high. Both native technology and low-code are tools in the hands of developers. The significance of tool change and reform is very different. Tool change means improvement of production methods and increase of production efficiency. You can also focus on another track - low code, the core logic is to use the code base to quickly copy the existing development samples, and the labor cost in the entire development process is close to zero.
JNPF relies on the principle of code development technology, so it is different from the traditional pain points of long development delivery cycle, difficult secondary development, and high technical threshold. Most of the application construction is realized by dragging and dropping controls, which is simple and easy to use. By providing developers with a visual application development environment, it reduces or eliminates the need for application development to write native code, and then realizes a convenient construction of applications. The development platform quickly assists R&D personnel to quickly build a set of solutions suitable for enterprise development.
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Opportunities for Chinese companies to break through in AIGC
In the hot land of AIGC, you and I are all pioneers. Even a big company like Baidu cannot avoid it. Wenxinyiyan is also adhering to the humble and low-key launch, but the domestic experience in secondary development of products is quite rich, and the application scenarios of AIGC are very broad. With the continuous improvement of the underlying large model A large amount of "data" in the low-code field is used for learning and training, and more and more accurate intelligent decisions will be output.
The corresponding "AIGC + low-code" will also burst out with more powerful capabilities, so there may be more and more interesting scenarios for applying GPT and other products in the future. Riveting enough energy to exert force, the future can be expected!