紫东太初4.0发布 国产大模型迈向“边看、边识、边思”新阶段

Core Insights - The first fully domestically developed deep reasoning model "Zidong Taichu" 4.0 was launched in Wuhan on September 19, showcasing advanced multimodal reasoning capabilities that surpass GPT-5, particularly in complex reasoning and tool usage with visual inputs [1][4]. Model Development - "Zidong Taichu" 4.0 represents a significant evolution from its predecessor 3.0, transitioning from "pure text reasoning" to "fine-grained multimodal semantic reasoning," achieving a threefold leap in capabilities [3][5]. - The model can perform complex reasoning tasks, such as determining the number of shots needed to win a snooker game by analyzing images of the game table [3]. Performance Metrics - In video multimodal applications, "Zidong Taichu" 4.0 can deeply understand 180-minute long videos, achieving state-of-the-art performance across six tasks, including video Q&A and content summarization [4]. - The model's reasoning speed has improved by approximately 15% compared to version 3.0, enhancing its application in industrial settings, such as high-precision laser welding technology [4][6]. Technological Innovations - The model incorporates three core technological innovations: low-cost data synthesis for real events, critical multi-round reflective learning, and difficulty-sensitive adaptive reinforcement learning, which collectively enhance training efficiency and reasoning performance by about 15% [5][6]. Industry Impact - The launch of the "Zidong Taichu Cloud" platform aims to convert the model's technological advantages into industrial value, providing comprehensive support for enterprises in computing power, application development, and implementation [6]. - The platform is positioned as the first native collaborative cloud for multimodal large models in China, facilitating the integration of AI capabilities into core business operations [6]. Economic Context - The current era is characterized as a computing power economy, where computing power, data, and algorithms are key resources driving the digital economy, highlighting the need for rapid iteration and widespread application of AI technologies [6].