In this article, I will share with you “how AI Medium platform can help enterprises digitalization and intelligent transformation”, as well as my experience in building AI medium platform.
Enterprise digitization aims to use digital technology to change enterprise business model, optimize production process and seek new business value. But not many companies are truly digital. So what do companies need to do on the journey of digitization?
From digital to intelligent
The first thing enterprises need to do is data connection, that is, data collection and sorting, as well as standardized and unified data operations, to form a unified data platform. Then based on these data to analyze, develop data indicators, and then based on these data indicators to carry out some mining and insight, finally according to the insight of the data to make decisions.
Intelligent enabling direction
- On a horizontal dimension, there are some generalised AI technologies, such as computer vision, CD and NRP, which is natural language processing. There is also acoustic processing, such as some general AI can be used in various fields.
- From the vertical perspective, enterprises can perform specialized analysis and mining of data in the vertical domain. For example, enterprises can go deep into a certain marketing scene and do some business exploration.
The combination of these two dimensions can produce a variety of intelligent enablement. The first type of empowerment is intelligent process management, such as intelligent operation, risk control in financial enterprises, some business assistants in the operation process, including the underlying technical operation and maintenance, etc.
The second category is the very familiar and much discussed intelligent precision marketing. For example, accurate recommendation, customer portrait, customer group analysis, and intelligent customer service.
The third category is intelligent decision making, which includes intelligent advisers, knowledge maps, and the use of ARTIFICIAL intelligence to report, analyze and predict trends, and finally help companies make decisions.
Therefore, intelligent empowerment has entered the daily research and development workflow of enterprises.
The pain point of intelligent construction in enterprises?
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The implementation process is complicated: there are many R&D links, repeated processes, and the lack of solidification, optimization and automation of processes, resulting in slow business response.
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Deployment and maintenance difficulties: model development and deployment are separated, and there is no unified operation, monitoring platform, and update and maintenance mechanism.
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Lack of feedback and updates: Production models lack continuous data feedback, resulting in model performance shifts over time and difficulty in updating.
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Problems of repeated model construction: “chimney type” development, repeated objectives, excessive duplication, lack of asset reuse and capacity precipitation.
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High input and low output: the project construction is relatively slow, with high input and low efficiency. After completion, the application scope is small and cannot be expanded.
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Lack of research management: lack of unified standards, scattered research forces, low resource utilization, lack of management of AI assets, easy loss.
The ideological structure of Centralization
The theory of Centralization was put forward by Ali several years ago. They carried out a series of centralization transformation in the enterprise. Ali emphasizes service precipitation, ability sharing, breaking system barriers, supporting small receptionists’ changing needs with the capabilities of large and medium receptionists, realizing agile support for receptionists’ business needs, and finally realizing rapid business innovation.
So what’s the middle stage we hear the most about? It’s data center.
The data center unified the standard of data, precipitated public data, and realized the integration of data materialization, standardization and unification. The fact it seems China is effective, because the data in the middle of curing down those who have the value of the assets and capabilities, with the help of the support tools, and unified the standardization of the constraint, can fully realize the outward and the ability to reuse and sharing, provide quick and efficient service, constantly meet the front desk depoliticization of all kinds of business requirements.
In general, after outputting assets and realizing relevant reuse and sharing, capabilities are precipitated again, brought into the middle stage, and then these resources are re-shared out again, ultimately achieving an organic cycle and intensive management of assets and capabilities.
Is the matter of ZHONGtai chemical helpful for AI research and development?
We build the AI middle stage, which connects with the business front stage, and relies on the support of the data side to provide a standardized and unified service externally. We only process standardized products using reusable capabilities and assets, and the whole process is traceable, maintainable, updatable, and can be effectively or reasonably recycled. This is the formation of AI platform.
Why does AI medium platform solve the problem
First of all, the AI intermediate platform can standardize the process specification for the complex implementation process, that is, enterprises can fully reuse algorithms and features, solidify through the feature engine, and then use data to retrain the model through reusable models and algorithms. The goal is to standardize, streamline and automate the complex implementation process, and speed up its learning process as much as possible.
In addition, for process-based deployment and maintenance, AI center can provide a set of standardized model packaging process, and external enterprises only need to maintain a unified service interface to achieve a unified platform for unified model operation and maintenance.
Enterprises can also set up a series of monitoring mechanisms and feedback mechanisms on the operating platform to collect and export data samples, define performance indicators and display reports on a regular basis. This relies on continuous monitoring of the service, while the AI middle platform implements continuous healthy feedback and updates. Finally, these continuous feedback updates will in turn play a role in optimizing the model in the process and automation of the complicated implementation process at the beginning.
All in all, AI is to make full use of the existing capabilities of the enterprise. When new requirements arise on the front end, the back end can quickly iterate over functionality with automated tools. In addition, the AI center can leverage some of the capabilities already in the enterprise to support the front end and make enterprise services more agile. If there are repeated requirements, AI can help enterprises directly use the existing services, through some simple transformation or packaging, to provide a fully reusable, fully shared service, to avoid repetitive construction.
AI zhongtai construction
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From the strategic dimension, enterprises must have clear determination and goals, as well as a series of long-term or short-term plans and guidelines for the implementation of the centralization of Taiwan.
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From the technical dimension, the centralization itself should have a core technical support, sometimes including the output of the centralization, which is the core of the implementation of the centralization.
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From the organizational dimension, in fact, it is through the adjustment of the organization to build the necessary organizational basis for the construction of the Central Taiwan, and facilitate the construction and implementation of the central Taiwan. But on the contrary, the construction and implementation of the center itself includes the intensive reshaping of the organization.
From the process dimension, the enterprise certainly needs to adapt and transform the relevant production process, so as to adapt to the construction of central Taiwan.
Author: Jing Yuxin, Creditease Institute of Technology
Reference examples of AI Zhongtai field construction route, as well as AI Zhongtai implementation cases, you can click “here” to view the full course video to learn ~