When the morning sunlight awakens the curtains, the speaker automatically broadcasts the weather conditions; The oven in the kitchen has started preheating according to the breakfast ingredients; At the same time, the coffee machine has automatically ground a fragrant latte. These scenes that once existed in science fiction movies have now flown into ordinary people's homes with the empowerment of AI. As AI technology continues to explore the topic of "home", the relationship between humans and household chores is constantly being reshaped - the era of "unmanned household chores" has arrived! Accelerating the Reshaping of Household Scenarios Recently, Haier Leader's Lazy Three Barrel Washing Machine, which achieved a delivery milestone of 130000 units, can be regarded as a benchmark case for AI driven innovation in the home appliance industry. When it comes to the birth of this product, Weng Zongyuan, General Manager of Haier Washing Machine Brand, shared his impressive user visits: after conducting research in more than 20 cities, it was found that over 50% of users have a "refined and lazy" demand, longing for "one machine, multiple cylinders" partitioned washing and care, to solve the problem of unhygienic mixed washing, and require strong washing power and easy operation. The user's challenge is Haier's problem, and with the deep empowerment of AI, the Haier Lazy Three Barrel Washing Machine has been born, achieving a breakthrough in the entire chain from demand insight to technological iteration: accurately capturing user pain points through intelligent algorithms and constructing multi-dimensional demand models; Relying on machine learning to optimize the design of the three tube structure, breaking through the bottleneck of traditional space utilization; By utilizing AI driven scenario based simulation testing, the product validation cycle has been significantly shortened. Weng Zongyuan introduced that this "demand technology verification" innovation loop formed under the support of AI not only gave birth to disruptive lazy laundry solutions, but also shortened the entire research and development cycle by 30%. AI drives the evolution of home appliances from "passive response" to "active service". Nowadays, basic functions such as washing clothes with washing machines and preserving food with refrigerators have become standard in the industry, and user demand is shifting towards "more worry free and precise" services. Xu Sheng, Director of Haier Smart Home Advanced Technology Center, introduced that this transformation essentially upgrades household chores from "manual operation" to "system hosting", continuously optimizes the processing path of household affairs through machine learning, and ultimately presents a disruptive experience of "devices actively serving people". AI reconstructs the home experience through the linkage of intelligent unmanned scenarios. At the China Home Appliances and Consumer Electronics Expo held in Shanghai in March this year, the deep penetration of AI technology into home scenes became a core highlight. Through the cross terminal intelligent IoT architecture, household appliances have broken through the single functional boundary and built a collaborative network covering the entire living space such as kitchen, balcony, living room, bedroom, etc. At the exhibition site, several leading companies represented by Haier showcased their "seamless home" solutions, marking a new stage in the home appliance industry with spatial intelligence as its core competitiveness, and setting a benchmark paradigm for scenario based implementation in the smart home industry. Take Haier's smart home kitchen scene as an example: when cooking porridge, the smart cigarette machine can temporarily answer the phone and leave. The smart cigarette machine can "watch the pot" in real time through AI vision. Once the rice porridge is detected boiling, it will immediately link the cooker to adjust the fire power to eliminate the risk of pot overflow; The instant the stove ignites, the smoke hood starts up, and during cooking, it can automatically adjust the air volume according to the altitude of the area, the air pressure of the public air duct, and the indoor smoke concentration, effectively preventing backflow. From single point intelligence to whole house linkage, AI is reshaping the relationship between people and homes. Recently, the State Council issued the "Opinions on Deepening the Implementation of the 'Artificial Intelligence+' Action," emphasizing the importance of data supply - massive, high-quality, and diverse data is the foundation for the leap in AI performance. Especially in the field of "unmanned household chores", with the continuous expansion of model parameter scale, problems such as low data quality, model limitations, and technical bottlenecks have become increasingly prominent, becoming the difficult and bottleneck points that the industry urgently needs to break through. Firstly, there is the issue of obtaining high-quality data. Taking the anti overflow function as an example, the seemingly simple task of "installing eyes on the stove" requires extremely complex data collection and testing work behind it. Xu Sheng introduced that in order to break through this technological bottleneck, Haier has invested a professional team of nearly 50 people, purchased more than 100 types of cookware and 300 types of pot lids, and constructed testing scenarios through different combinations. At the same time, multiple variables such as the placement of cookware on the stove, lighting conditions in the kitchen, and the characteristics of the ingredients need to be considered. Without a high-quality data foundation, even the most advanced models are difficult to achieve precise identification and early warning. The second challenge is the implementation of model autonomy. The localized deployment characteristics of home scenarios pose special requirements for model selection. Most household appliances rely on home scenarios with limited computing power, making model selection particularly crucial. Xu Sheng mentioned that different models will produce different experimental results, and the key challenge facing the industry is how to achieve model autonomy under limited computing power, ensuring stable operation in various environments. Finally, the solution to the AI illusion problem. The phenomenon of AI "seriously talking nonsense" is called AI illusion. Research shows that the illusion rate of some large models can reach as high as 20%, which also reflects the urgency and complexity of solving AI illusion problems. In home appliance control scenarios, AI illusions may lead to security risks. For example, in the scenario of stove fire control, if AI experiences hallucinations and misjudgments, it may increase the fire when it should have been reduced, or turn off the stove when it should not have been turned off, which can pose safety risks or affect cooking effectiveness. It is reported that the current related industries mainly address this challenge through the integration of multiple algorithms. By cross checking multiple algorithms, when one algorithm experiences hallucinations, other algorithms can correct it. In addition, breakthroughs in AI vision technology are also crucial for the realization of "unmanned household chores". Vision is the most important perception for humans. Currently, traditional household appliances can replace 80% of household chores, but the remaining 20% still require breakthroughs in visual AI technology. The industry is actively promoting technological breakthroughs. It is reported that Haier has taken the lead in releasing the "AI Eye" technology in the industry, which endows home televisions with perceptual abilities to truly "understand" the home environment and user needs. This also marks a major breakthrough in the field of visual AI in the home appliance industry. The open collaborative innovation ecosystem promotes the transition of "unmanned household chores" from "pilot scenarios" to "comprehensive popularization". The entire industry needs to collaborate to build an innovation system that covers standards, cooperation, technology, and research and application, forming a virtuous cycle of "technological breakthroughs, scenario implementation, and ecological co construction". At the level of data collection standards, standardization is a prerequisite for the high-quality development of the industry. At present, the standardization of data collection has become an industry consensus - from enterprise standards to industry standards and then to national standards, a hierarchical standard system is being formed. Xu Sheng introduced that Haier has taken the lead in promoting internal data collection standards to group standards, industry standards, and even national standards. At the same time, it has deeply participated in the formulation of national standards and regulations, laying a solid bottom line for data quality. Open cooperation is an important driving force for breaking down technological barriers and accelerating the implementation of scenarios. Unmanned household chores involve multiple fields such as AI algorithms, control technology, and scene design, making it difficult for a single enterprise to cover all aspects. If the data flow in real scenarios is the protein for training AI, ecological boundaryless co creation is an inevitable choice to further accelerate the development of industrial ecology, and to achieve experience and technological upgrades through continuous evolution and iteration. In recent years, the cooperation mode of "technology+scenario" in the industry has gradually increased: the accumulation of robot companies in ontology research and algorithm design complements the advantages of home appliance companies in scenario understanding and user needs. The ecological integration between enterprises can not only accelerate the landing of products, but also promote the industry to shift from "single point competition" to "ecological win-win". Keeping up with the pulse of cutting-edge technology and continuously deepening innovation momentum has become a key engine for industry development. Currently, the VLA multimodal large model that integrates visual, language, and action capabilities is leading the AI and robotics fields towards a new stage of "perception decision execution" integration. This technological breakthrough provides a full chain solution for "unmanned household" scenarios, from environment recognition to task implementation, by constructing an intelligent closed loop of "understanding scenarios, understanding requirements, and precise execution". It is worth noting that in order to bridge the "last mile" of unmanned household chores, robots must be a key link. In the future, we will enter an era where robots dominate household chores. As Zhou Yunjie, Chairman and CEO of Haier Group, said, "Different segmented scenarios can develop specialized robots in different vertical domains, and each household may have N robots. ”These highly intelligent robots will efficiently collaborate with the AI appliances they are compatible with, and the intelligent model of "robot led+AI appliance collaboration" will reshape human life. Compared with technology-based startups, leading home appliance companies that deeply cultivate the consumer end rely on their complete industry chain capabilities and user demand insights to demonstrate unique differentiation advantages, and will also become the backbone of promoting the large-scale implementation of "unmanned household chores". (New Society)