In today’s era, artificial intelligence is reshaping all walks of life at an unprecedented speed.
However, in the field of industrial automation, the lifeline of the national economy, the deep integration of AI and PLC has fallen into a structural deadlock.
Let’s first look at the dilemma of mainstream AI tools in industrial applications.
On the consumer side, AI is developing rapidly. For example, ByteDance’s Doubao can write weekly reports, make PPT, etc., Wen Xin Yiyan can write poems and paintings, and Tongyi Qianwen can analyze financial reports, etc.
But on the industrial side, the situation is completely different.
According to relevant reports, although some industrial enterprises have deployed AI, the proportion of actual large-scale applications is low.
Industrial intelligence faces core obstacles such as the difficulty in transforming single-point applications into an overall manufacturing model and the insufficient depth of integration between AI and manufacturing mechanisms.
There is a fundamental mismatch between the capability structure of current mainstream AI tools and the rigid needs of industrial sites.
Industrial sites require intelligence that is deterministic, real-time, interpretable, and process understanding. However, large models are essentially probabilistic systems with delays and “black box” characteristics that cannot meet the needs of industrial sites.
In addition, the implementation of AI in industrial sites also faces practical difficulties such as data fragmentation, high costs, difficulty in safety certification, and talent shortages.
Look at the AI dilemma of mainstream PLC.
The global PLC market is highly concentrated, and Inovance Technology has performed well in the domestic camp.
However, whether it is an imported or domestic PLC, most of its architectural design still remains in the previous era.
The core problem is that PLC lacks native integration of AI chips, and the problem of “AI programming and core screen two skins” has existed for a long time, making it difficult to deeply integrate AI and PLC.
In this context, the complementary cooperation between Inovance Technology and ByteDance is particularly urgent and necessary.
Inovance Technology is the company that “best understands the industrial body” in China’s industrial automation field. It has a complete automation product matrix, rich process data and scenario experience, and has a firm AI strategic direction.
But Inovance lacks a powerful “AI brain”.
ByteDance is strong in the field of AI, with industry-leading large model algorithms, powerful cloud computing power, etc., but it lacks practical application experience in the field of industrial automation, that is, it lacks an “industrial body.”
The cooperation between the two has threefold inevitability.
From a technical logic, the deep integration of AI and PLC requires full-stack reconstruction. Inovance and Byte have industrial site understanding capabilities and AI algorithm and computing capabilities respectively. Only by combining them can we achieve the road of “AI native PLC”.
Judging from the time window, Qualcomm has released industrial-grade AI chips. Whoever can be the first to launch PLC products based on AI native architecture will have the say in future industrial automation, leaving little time for Inovance and Byte.
From a national strategic level, the autonomy and controllability of industrial automation is crucial, and the cooperation between Inovance and Byte is related to the future of China’s industrial intelligence.
Specific cooperation directions include joint research and development of AI native PLC chip solutions, development of industrial vertical large models, creation of AI native PLC programming environments, and establishment of an industrial AI application ecosystem.
If Inovance and Byte can work together, China is expected to change lanes and overtake on the “AI native PLC” track.
As a front-line engineer, I look forward to the day when AI can truly become the “intelligent partner” of PLC, giving the PLC in the workshop an “industrial brain.”
