Core Insights - The article discusses the launch of the GLM-4.5V visual reasoning model by Zhipu AI, which is claimed to be the best-performing model globally with 100 billion parameters, capable of accurately identifying image details and inferring background information without relying on search tools [1][5] - The competition in visual reasoning capabilities among major AI companies, including OpenAI, Google, and domestic players like Doubao and Tongyi Qianwen, is highlighted, emphasizing the growing importance of multimodal capabilities in AI models [1][5] - Concerns regarding privacy risks associated with AI's ability to pinpoint locations from images are raised, especially in light of previous models that have sparked worries about "opening the box" [1][5][6] Model Performance Summary - In a practical test, Doubao achieved a 100% accuracy rate in identifying locations from images, while Zhipu's GLM-4.5V had a 60% accuracy rate, and Tongyi Qianwen's QVQ-Max only reached 20% [2][3] - The models were tested on five images with varying levels of identifiable landmarks, showing that typical landmark photos were easier to identify, while more ambiguous images led to varied performance among the models [3][4] - Doubao's superior performance is attributed to its ability to connect to the internet for real-time data retrieval, enhancing its accuracy in location identification [4][5] Technical Developments - The article notes that visual reasoning has become a competitive focus for AI models, with several new models being released this year, including OpenAI's o3 and o4-mini, and Google's Gemini 2.5 pro, all showcasing advanced visual reasoning capabilities [5][6] - Zhipu AI's GLM-4.5V reportedly outperformed 99% of human players in a global competition, demonstrating its advanced capabilities in inferring geographic coordinates from images [6] Privacy Concerns - The article highlights a study indicating that advanced multimodal models, including those from OpenAI and Google, pose significant privacy risks by lowering the barriers for non-experts to extract location data from social media images [6][7] - Experts suggest that AI companies should implement safety boundaries for image analysis capabilities to mitigate privacy risks, such as restricting access to sensitive data and limiting the analysis of potentially dangerous requests [7][8]