At the recent seventh China Liaoning International Fair for Investment and Trade, one phenomenon was easy to spot: there were plenty of AI applications on display, but they looked less and less like the AI we are used to.

There were no wall-to-wall chat interfaces, and no clusters of demonstrations writing poems or generating copy. Walking through the exhibition areas, visitors saw intelligent robots from Shenyang, multi-machine collaborative robotic arms from Jiangsu, smart sensors and underwater robots from Dandong, industrial internet systems from Yingkou, and green computing power from Chaoyang. AI is no longer a series of isolated new technology exhibits, but increasingly something that "grows" inside industries.

When AI looks less and less like AI, that is precisely a sign that the technology is maturing. AI will not truly change the world only on screens. The next, bigger test is likely to take place in factories, ports, mines and oceans, and this offers a completely new perspective for reunderstanding Liaoning's development strengths.

Liaoning has industries including steel, petrochemicals, automobiles, aviation, shipbuilding, machine tools and robotics, as well as enormous production lines, industrial equipment and a large engineering workforce. In the past, these were called the "old industrial foundation." Seen from a different angle today, they are giving AI its form and shape.

Without workshops, industrial AI would not know what a production takt is. Without large-scale equipment, it would not know how to predict faults. Without ports and oceans, it would also struggle to learn perception and decision-making in complex environments. Algorithms give AI its brain, but industry gives AI its hands and feet.

Inside an automobile factory, it must learn machine vision and quality inspection. Inside petrochemical facilities, it must understand safety boundaries and complex processes. In shipbuilding and marine engineering, it must face sea conditions, corrosion and remote operations. Therefore, Liaoning's advantage is not only that it has "many scenarios," but that these scenarios are sufficiently complex, real and scaled into industrialization.

In the internet era, platforms trained algorithms with massive numbers of users. In the era of industrial intelligence, production lines can likewise train AI. A factory that has operated for decades has accumulated practical experience that forms an industrial dataset thicker than any textbook.

Of course, possessing a strong industrial base does not automatically translate into an AI development advantage. To truly turn the "old foundation" into a "new base" for digital transformation, it is still necessary to connect data, unify standards, open scenarios, and push universities, research institutes and innovative enterprises to genuinely go down to the workshop front line.

The moving robotic arms and inspection robots at the Liaoning fair ultimately cannot remain only under the spotlight. They must walk out of the exhibition hall and enter production lines to solve the most practical problems: yield rates, energy consumption, safety and efficiency.

Whether AI can be deployed still depends on how many old problems it solves for factories. This is also the differentiated path Liaoning can take in participating in international AI competition.