On the afternoon of November 7, 2025, the School of Statistics and Data Science at Shanghai University of Finance and Economics successfully held a special forum on "AI Rapid Landing Projects and Overseas Technology" in the Tijiu Classroom of Wudong Road Campus. This forum specially invited Mr. Wang Ying, a master of natural language processing from Nanjing University, Internet Sailing and AI new media entrepreneur, as the keynote speaker, and deeply shared the practical path of AI products from conception to implementation, from local to global deployment.
At the beginning of the lecture, Mr. Wang started with the common work scenario of "AI automatically generating PPT", pointing out that big models are comprehensively changing the way knowledge production and content creation are carried out, significantly shortening the cycle of product prototype construction and project verification. He further pointed out that current domestic AI products face strict content review and filing requirements in the online process, while overseas markets are relatively more flexible in model usage, application deployment, and user access. Therefore, going global is not only a form of business expansion, but also an important strategic window for AI products to quickly trial and error, verify requirements, and shorten iteration cycles. At the macro level, he combines inflation levels, exchange rate fluctuations, and global technology industry cycles to analyze that the user base, payment ability, and open ecosystem of overseas markets provide a favorable market environment for AI entrepreneurship.
Later, Mr. Wang proposed the "three-tier model of Internet products", namely, the traffic layer, the technology layer and the team layer. He emphasized that the true success of a product depends on whether it accurately meets real needs, rather than the flashy stacking of technology itself. In the era of big models, by utilizing AI assisted front-end interface generation, back-end business logic construction, and algorithm module invocation, entrepreneurs can complete the minimum feasible product and conduct online testing within a few days, significantly reducing development costs and trial and error risks, and accelerating the conversion path from "ideas" to "products".
In terms of traffic and market expansion, Mr. Wang has sorted out the ecological differences of major overseas content platforms such as Reddit, YouTube, X, and TikTok, corresponding to technology community diffusion, in-depth knowledge dissemination, public opinion heat guidance, and rapid rise of short videos. He explained the cultivation of account ecology, content matrix construction, and private domain transformation path based on practical project experience, and introduced the commonly used AI short video automation production toolchain and application strategy, demonstrating the full process growth mechanism from "public domain reach" to "private domain takeover" for students.
On the technical implementation path, Mr. Wang provided a systematic explanation from front-end interface generation, back-end framework construction to model local/cloud deployment, and clearly presented the technological evolution of AI projects from the budding stage of single server to cluster scale through "initial single machine deployment → database migration → static page optimization → containerization and automation". He also pointed out that a balance needs to be struck between lightweight deployment and high concurrency architecture in different application scenarios, and technical decisions should revolve around business requirements and cost efficiency.
Regarding team building and recruitment, Mr. Wang specifically mentioned that as AI tools improve content and output efficiency, the value of traditional resume screening is declining, and companies are placing more emphasis on candidates' practical abilities, learning speed, and team fit. He suggested that students should do more real projects during their school years to accumulate and prove their achievements, and cultivate collaboration, iteration, and self drive abilities in teams, which will become the core competitiveness of the AI era.
In the Q&A session, students discussed entrepreneurship risk assessment, career path selection, and AI job competency requirements. Regarding the question of "how to determine whether one is suitable for entrepreneurship", Mr. Wang shared his personal experience and pointed out that entrepreneurial decisions should be based on long-term consistency between life status, existing project foundation, interests, habits, and career direction. He emphasized that "being able to tinker, persevere, and practice" is more important than "thinking or not".
This forum provides valuable opportunities for students to understand the logic of entrepreneurship and the path of technology implementation in the AI era through case analysis, experience sharing, and on-site interaction. It further broadens students' understanding of the AI going global ecosystem and innovation models. The forum came to a successful conclusion amidst lively discussions.
Author: Qiu Chenyi
Image provided by: Du Yuxi
