A：We believe that the big opportunity for future AI development lies in the gradual penetration of AI capabilities into the physical world and the acquisition of physical form, which allows AI to penetrate into daily life to perform various tasks, not only with robots, but also with all kinds of intelligent hardware. In addition, the intelligent body into the vertical industry transformation, can significantly improve efficiency. Our company is positioned as an intelligent species platform company, committed to AI hardware, robot services and traditional industry depth transformation and other ways, continue to accumulate data and scene experience, to build a common physical world model. At the same time, we build the world model (Word Action Model) in the center, build the data flywheel through real-world scenarios such as industry scenarios, robot scenarios and AI hardware scenarios, and have a full-stack closed-loop team to achieve these goals.

A：We are more like Fake in terms of differentiated positioning, because Fake is not only a AI assistant company, but also focuses on artificial intelligence applications in vertical fields. Our team has diverse backgrounds and strong complementarities, including top AI scientists and industry elites with practical experience. At present, we have a layout in the e-commerce business, and plan to transform it into a more B- side output logic to help traditional enterprises solve practical problems in the process of digital transformation.

A：Traditional enterprises will face the problem that the No. 1 leadership does not understand the technology or cannot effectively promote the transformation, and the fundamental problem is difficult to reach in the process of bottom-up transformation. In response, our approach is to drive change from the top, break down hierarchical barriers, and achieve true AI-driven organizational change by integrating existing resources, such as rebuilding systems and replacing old systems and technical maintainers.

A：When we work with partners, we will embed the new system directly into their system, and gradually embed the entire business module into different partners. In this way, the partners have a new source of income at the same time, the original human system is no longer needed, thereby achieving cost reduction.

A：After the transformation, most of our revenue will come from the purchase of tokens in the market and value-added and service output. We provide partners with a unified embedded system and corresponding charging model, so that the company's model becomes lighter.

A：In the field of AI-side hardware, our ultimate goal is to solve consumer needs by providing intelligences to meet the needs. For example, a smart body solution is built in a restaurant scenario and co-built with partners, and then output to a smarter solution for the restaurant.

A：The end-side hardware obtains user data and provides intelligent services. The hardware is only the entrance, and more later services are used to meet user needs. By occupying the entrance of the home (such as a robot), the application scenario of the home can be extended to form a commercial closed loop.

A：Accumulate data in the process of running the business model, which will become the basis for building large models or large models of the physical world in the future, forming a positive closed loop through technology accumulation, scenario-driven, model updates and real data reflux.

A：We plan to achieve a completely unmanned unmanned restaurant in the next one or two months, and launch a takeaway service. At the same time, the use of restaurant cloud skills and language ability to promote to other industries such as 4S stores, cinemas, and even cross-industry applications to the medical industry.

A：We hope to open up various scenes by 2026 and start the unmanned restaurant and offline display store projects. By the second phase, it is expected to cover 200 restaurants and work with 200 ecological partners to achieve more goals until 2018.

A：We will continue to deal with these problems, work with partners in the industry to solve supply chain and mass production problems, and promote technology research and development through our own R & D team and partners, positioning ourselves as a financial technology company in the physical world.

A：Technology base refers to the data model and intelligent body that we are building, which is neither completely virtual generation nor based on real data. It is an economic entity that combines practical application scenarios, through data collection and intelligent output, and aims to serve the B- side scenario, become the world model in the medium term, and eventually enter thousands of households.

A：Startups have an advantage in data integration, and most startups obtain data mainly through ontology output, making it difficult to integrate resources across companies. And we can be more flexible in vertical scenes and applications, and the speed is relatively fast. In addition, because the AI hardware and robotics fields are not completely monopolized, and user needs are diverse, startups have the opportunity to make breakthroughs in specific fields and products.

A：Our development path is to start with smaller areas such as AI images or toys, collect user data for training models, and then gradually expand the application scenarios. Compared with traditional hardware manufacturers, start-up companies have more advantages in providing products combining software and hardware and follow-up commodity services, can better solve the actual needs of users, and combine goods and services through the platform.

A：We plan to collect large amounts of data in specific scenarios such as restaurants through cooperation, and set up special training venues for deep learning training. Explore how to solve the remaining problems in a semi-automated environment and achieve truly digital solutions with local companies in deep collaboration. The restaurant scene has the characteristics of low standardization and prominent food safety problems, which are suitable for robots to solve. Moreover, with the development of the chain catering industry, the quality of chefs and service personnel is difficult to maintain consistency, and the cost of robots is relatively low, which can achieve significant economic benefits in the unit economic model. At the same time, western food has a high degree of standardization, which is also suitable for digital transformation in a similar way.

A：So far we have a video that shows a two-armed robot cooking in a restaurant environment. By adding agents, robots can imitate human learning, adjust their actions to the actual situation, and even improve their mistakes by trying and learning.