Step into the waic 2025The exhibition hall is filled with a strong intelligent atmosphere, and the most futuristic cutting-edge technologies are displayed at all booths.
Among them, a booth focusing on industrial Internet caught my attention.
What does traditional industry have to do with AI?
In the exhibition area of COSMOPlat in Kaos, various industrial data are beating on electronic screens. On the twin manufacturing integration platform, virtual sections such as factory twins, production line simulations, and value chain simulations work in an orderly manner, simulating the operation of physical factories, allowing visitors to clearly see the changes from the overall layout to the details of the production line in the twin world. In front of the AI+ smart chemical smart sand table in the center of the booth, visitors are scanning the scene with iPads, and the equipment is displayed on the screen in real time as the camera moveshot spot, tap to enter the digital content page to view detailed information such as production line parameters and energy consumption data.
At the entrance of the exhibition area, the staff and the Haier brothers on the virtual screen asked and answered, explaining to the audience in the exhibition area various knowledge in the Kaos booth, which was full of fun.
Compared with other booths, Kaos has precipitated a pragmatic and calm temperament. The latest achievements of “AI + Industrial Internet” displayed by it make people feel the inevitability of moving from the traditional industrial Internet era to the era of AI large models: on the one hand, the growth bottleneck faced by traditional industrial Internet platforms, and on the other hand, the new possibilities brought by AI large models. In the face of new challenges and needs, Kaos, based on Haier’s 40 years of manufacturing experience, is using the Tianzhi industrial model as the engine to re-explore the vitality of traditional industries in the AI era.
So, in the AI era, what challenges does the traditional industrial Internet usher in? How does the industrial Internet model sink to empower thousands of enterprises?
The variety of intelligent applications at the exhibition makes people think: What variables has the emergence of AI brought to the traditional industrial Internet?WhyIt needs a large vertical model so urgently?
On the one hand, traditional machine learning algorithms and small models face dual constraints of ability and cost. Just like a person has multiple senses, but it is difficult to make accurate judgments because the brain cannot integrate information, small models are often inadequate in complex industrial scenarios. Moreover, the development cost is equally prohibitive. Due to the high degree of differentiation of industrial scenarios, it is difficult for standardized platforms to meet the individual needs of enterprises. When enterprises try to customize and develop small models, they often face the dilemma of long cycles and high costs, which discourages many small and medium-sized enterprises eager for digital transformation.
On the other hand, there is a gap in professional adaptation for general large models. Although the general large model performs well in some fields, it is often unacclimatized due to the lack of industry expertise in industrial scenarios. The industrial field has extremely strict requirements for reliability, and the availability of algorithm recognition must reach more than 99%. In the face of high standards, general large models often require in-depth customization, but this process not only consumes resources, but may also be twice the result with half the effort due to lack of industry experience.
It is this dilemma of “small models are not enough, large models are not easy to use” that has given birth to the rise of vertical large models. The vertical domain large model can not only realize multi-source data fusion, but also internalize the industry knowledge graph, providing tailor-made intelligent solutions for the industrial Internet.
According to Deloitte’s 2024 Industrial AI White Paper, 78% of manufacturing companies believe that multimodal intelligence is the key to breaking through the current technology ceiling, but less than 15% of mature solutions in the industry are available. The significant gap between supply and demand shows that it is imminent for the industrial Internet to embrace AI variables.
As Zhou Yunjie, chairman and CEO of Haier Group, said, the industrial Internet cannot only be an “industrial version of e-commerce” with a width of 100 meters and a depth of 1 meter, but must be deep. This “deep” refers to the depth of intelligence and industry knowledge. Obviously, to break through these bottlenecks, the industrial Internet needs a complete brain upgrade.
With the arrival of AI, the industrial Internet is expected to achieve a qualitative leap, and there is an urgent need to introduce large model technology. However, the industrial Internet has extremely high requirements for large models, which not only requires strong computing power, but also requires in-depth industry knowledge and accurate scenario adaptation, which discourages many companies and urgently needs someone to break the situation.
In this context, as a leading domestic industrial Internet brand, Kaos has given its own industry solution.
The first is the breakthrough. Industrial Internet manufacturing enterprises have accumulated professional data and knowledge from all walks of life for decades, calling for a vertical model that understands industry better, but who can combine the industrial Internet with the large model? At this critical moment, Kaos took the lead in creating the first vertical model based on the industrial Internet, the “Tianzhi Industrial Model”, laying the scientific and technological foundation of the industry.
The first step of Kaos is to establish a unified data base, open up heterogeneous data sources within the enterprise, and let silent data start a dialogue, which is inseparable from Haier Group’s 40 years of manufacturing experience and platform digital practice. Furthermore, the large model integrates various industrial data elements, penetrates multiple industrial application scenarios, and can empower home appliances, petrochemicals, energy and other fields. Taking the industry model in energy and carbon as an example, Kaos integrates 80TB+ modal industrial data and 100 billion parameters, which is equivalent to building a central nervous system for giants, so that all sensory information can be gathered in the brain.
In the face of the problem of insufficient intelligence in the industry, Kaos has achieved in-depth precipitation of professional knowledge with industrial large models. Unlike the broad but not refined characteristics of general large models, industrial scenarios require real expert-level intelligence. To this end, the Tianzhi industrial model integrates massive industrial knowledge, mechanism models and expert algorithms, and currently covers more than 4,700 mechanism models and more than 200 expert algorithms, so that the model has expert-level thinking ability.
Taking the Kaos Tianzhi Energy Carbon Model as an example, as the first 100 billion parameter energy and carbon model derived from the practice of sustainable lighthouse factories, it has accumulated more than 30 years of energy management experience, learned more than 300 rich project cases, and realized intelligent knowledge Q&A, data analysis, risk prediction and energy diagnosis, just like an experienced old expert in the energy industry.
However, the technological breakthrough of large models is only the starting point. After successfully breaking through, how to allow small and medium-sized enterprises with limited capital and technical capabilities to enjoy the dividends of large models is another major challenge.
In the face of the differentiated needs of thousands of enterprises, Kaos has given a variety of solutions. Taking the COSMO-Sphere enterprise-level industrial Internet platform as an example, the platform adopts a “1+N” modular architecture, which allows enterprises to assemble their digital systems on demand like building blocks. At the same time, the low-code and AI provided by the platformtoolIt allows business personnel who are not good at programming to quickly develop intelligent applications.
Not only enterprises, but the key to AI empowerment is to make everyone use it equally. Therefore, sinking to every grassroots technical employee has become an indispensable part.
In order to make it easier to use, Kaos has launched more than 110 agent development tools. For example, in the energy field, the industry large model forms the human-computer interaction service agent “Energy Xiaozhi”. Managers can interact with them online 24 hours a day through voice, graphics and text, and can query energy consumption data and generate energy-saving suggestions without manually finding menus.
Kaos’ AI practice transforms the platform from a passive tool into an active and self-optimizing intelligent partner. This means that AI is not meant to replace people, but to become people’s right-hand men. The sinking of large industrial models is not only the popularization of technology, but also the democratization of intelligence. When AI moves from the technology base to the front line of the workshop, the next stop of the industrial Internet will be a new era of “everyone can use it and be intelligent everywhere”.
After looking at the technology-enabled solutions, let’s take a look at the actual landing effect.
At the Kaos booth, I saw the real stories of what happened after AI entered the factory.
On the Loess Plateau in Shaanxi, a large petrochemical model with hundreds of billions of parameters is quietly changing the fate of a century-old oilfield. By extending the Yunxiang Industrial Internet platform, the oil well diagnosis that relied on manual labor in the past has been automated, and the production efficiency has increased by an average of 20%.
We saw the model smart park where the Kaos Tianzhi Energy Carbon model landed on the spot.
In the model smart park of the Kaos Energy booth, the smart energy general control center is in the center, surrounded by substations, wind power stations, office areas and other buildings. The park is dominated by blue, the green belt is staggered, and the atmosphere of intelligence, low-carbon and energy-saving is coming. Such a smart park can reduce carbon emissions by a total of 550 million tons and save 200 million kWh of electricity.
On the other side of the exhibition area, a number of “firsts” on the large screen of the lighthouse factory plan are particularly eye-catching.
To put it simply, Kaos’s lighthouse factory construction consulting service is a set of full-process service packages to help enterprises upgrade traditional factories to “smart factories”, with the goal of making factories more efficient, more economical and more profitable.
With the help of Kaos, Haier Shanghai Washing Machine Interconnection Factory shortened the construction cycle by 6 months and increased manufacturing efficiency by 57%, creating the first in the washing machine industryMetaversethe factory of the future; At the Kaos Chuangzhiwu United Fertilizer Interconnection Factory, the factory order delivery cycle has been shortened by 50% and the on-site defect rate has been reduced by 33%, making it the first lighthouse factory in the domestic intelligent controller industry. Haier Tianjin Washing Machine Connected Factory focuses on green manufacturing and has become China’s first “sustainable lighthouse factory”, reducing energy consumption by 35%.
From these tangible results, we can clearly feel that “AI + Industrial Internet” is no longer a distant concept, but an ongoing change that can bring real value. From construction cycle to production efficiency, from product quality to delivery speed, it is becoming a new quality productivity in the industrial field, driving the entire manufacturing industry to a higher level.
As I left the exhibition hall, a word echoed repeatedly in my mind: integration. What we see is not a simple “industry + AI”, but AI as a way of thinking that is completely integrated into the bloodline of industry. The industrial Internet provides scenarios and data, and AI provides wisdom and decision-making, both of which are indispensable and mutually achieve.
Perhaps, we are at a critical juncture from quantitative change to qualitative change – the AI sudden change of the industrial Internet. The deep integration of industrial Internet and AI is the general trend and the only way for the high-quality development of the industrial economy.
To ensure that the traditional industrial Internet is not outdated in the new era, it is inseparable from the escort of AI. Industrial workers will form a new collaborative relationship with AI, so that productivity will be liberated like never before.
Seeing this trend, Kaos is guided by high value, and through the technical base of Tianzhi industrial large model, the large model capabilities are sunk to the production line of thousands of industries, so that enterprises of different sizes can enjoy technological dividends and jointly promote the development of industrial production in a more efficient, intelligent and sustainable direction.
The above is the next stop of the industrial Internet: the details of Kaos’ AI large model solution, for more information, please pay attention to other related articles on the PHP Chinese website!
