Core Insights - The core challenge for Chinese companies going global is to establish emotional connections with overseas consumers as competition shifts from "traffic acquisition" to "emotional connection" [1][3]. Group 1: Industry Context - The 2024 foreign direct investment from China is expected to grow by 16.1% year-on-year, with total exports exceeding 12 trillion yuan [4]. - The globalization of Chinese brands is increasingly focused on brand value, moving from "Made in China" to "Chinese Brands" [4]. - Cultural differences in markets pose significant challenges for brand communication, as traditional analysis methods are costly and slow [4]. Group 2: Technological Innovations - Minglue Technology's self-developed VLA model, named Mano, ranks first in the Special Model track and second in the general model track, enabling precise data extraction and market analysis [8]. - The HMLLM model, nominated for the ACM MM 2024 Best Paper, quantifies emotional responses scientifically, achieving over 89% consistency with human subjective feelings [11]. - The DeepMiner platform utilizes multi-agent collaboration to analyze emotional and understanding effects of videos and advertisements across different demographics [13]. Group 3: Application and Impact - The RaaS (Results as a Service) model is exemplified by Minglue Technology's platform, which has significantly reduced creative evaluation time from 3 days to 30 minutes, increasing efficiency by 99% [15]. - The platform has improved material effectiveness from 30% to 70%, a 133% increase, and boosted client renewal rates by 40% [15]. - Minglue Technology's solutions are aimed at overcoming cultural barriers and creative bottlenecks in internationalization, contributing to the development of the Yangtze River Delta as an "AI+" innovation hub [16][21]. Group 4: Recognition and Future Prospects - Minglue Technology won the "Special Award" at the CICAS competition, showcasing its innovative project in AI-driven marketing and emotional connection [1][22]. - The company will represent the Suzhou special competition in the national finals scheduled for late January 2026, continuing to leverage technological innovation for enhancing brand value in the globalization process [22].

Core Viewpoint - The article highlights the journey of Wu Minghui, the founder of Minglue Technology, emphasizing his technical background, entrepreneurial challenges, and the evolution of his company towards AI-driven solutions, particularly focusing on trust and data credibility in business decision-making. Group 1: Entrepreneurial Journey - Wu Minghui is portrayed as a typical "scholar-type" entrepreneur with a strong technical background, having excelled in mathematics and computer science [1][7] - The company experienced significant ups and downs, including a dramatic downturn where it struggled to pay severance to employees, leading to negative public perception [1][39][46] - After nearly two decades of exploration in the business world, Wu has focused on the core question of what constitutes trustworthy data [3][24] Group 2: Product Development and Innovation - Minglue Technology recently launched the multi-modal foundational model web GUI intelligent agent, Mano, which achieved state-of-the-art performance in international benchmarks [1][2] - The proprietary large model product line, DeepMiner, aims to address the challenge of making AI agents trustworthy, explainable, and traceable in enterprise decision-making [2][68] - DeepMiner is designed to connect credible data sources, enabling businesses to make informed decisions based on reliable data analysis [68][69] Group 3: Strategic Insights and Reflections - Wu reflects on the importance of trust in data and the need for AI to act as a gatekeeper in business decisions [4][66] - The article discusses the strategic errors made during the company's rapid expansion, emphasizing the need for a controlled strategic pace [50][51] - Wu acknowledges the lessons learned from past failures, particularly the necessity of aligning team goals and maintaining trust within the organization [54][57]

Core Viewpoint - Minglue Technology's proprietary GUI model, Mano, has achieved record-breaking SOTA results in the recognized benchmarks Mind2Web and OSWorld, establishing a new paradigm for GUI intelligent agents through innovations in online reinforcement learning and automatic data collection [1][14][23]. Group 1: Performance Achievements - Mano achieved a success rate of 40.1% in the OSWorld-Verified benchmark, surpassing other models such as qwen and GUI-Owl [10][19]. - In the Mind2Web benchmark, Mano demonstrated superior performance across various metrics, including element accuracy and step success rate, significantly outperforming all other SOTA methods [18][15]. - The model's success rate in OSWorld-Verified reached 41.6±0.7%, marking an approximate 7 percentage point improvement over competitors [21][19]. Group 2: Innovations and Methodology - Mano introduces online reinforcement learning as a novel training paradigm in the GUI interaction field, enhancing its performance in dynamic environments [22][23]. - The model's architecture consists of three main components: exploration module, processing flow, and optimization process, which collectively improve its reasoning and adaptability [25][26]. - The automatic data collection method developed by the technical team significantly enhances the efficiency and accuracy of data acquisition, allowing for the generation of high-quality interaction trajectory data [48][49]. Group 3: Market Context and Future Directions - The demand for AI agents is expected to surge by 2025, positioning Mano as a key player in differentiated competition by accessing data sources that other agents cannot reach [59][63]. - Minglue Technology plans to continue exploring areas such as data collection, training integration, and CAPTCHA handling to further optimize Mano for real-world applications [66].