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张哲:数据帮助解决算法模型落地的最后一公里问题
Bei Ke Cai Jing· 2025-07-12 04:07
Core Insights - The AI industry is experiencing significant changes, with a shift from single-modal to multi-modal models and a transition from general to vertical application scenarios [5][6] - The rise of large models has initiated the integration of AI with various industries, highlighting the importance of high-quality data to address the "last mile" problem in algorithm implementation [6][7] Group 1: AI Model Development - AI large models are evolving towards multi-modal capabilities, enhancing their application in specific verticals [5] - The introduction of Chain of Thought (CoT) technology allows models to improve their accuracy and reliability by shifting from "fast thinking" to "slow thinking" [5] Group 2: Data Demand and Market Dynamics - The demand for training data in the AI sector is changing, driven by the need for high-quality data to solve practical implementation challenges [6] - The domestic AI data market in China represents only a small portion of the global market, with significant opportunities abroad [7] Group 3: Company Profile - Haitai Ruisheng, established in 2005, is one of the earliest providers of AI training data solutions in China and is currently the only publicly listed company in this sector [7] - The company has seen substantial growth in its global business, with nearly half of its revenue coming from overseas in the previous year [7]
从资源高地向产业高地转型 凉山:圈链“辩证法”
Si Chuan Ri Bao· 2025-06-10 06:15
Core Viewpoint - Liangshan Prefecture is transitioning from a resource-rich area to an industrial powerhouse, focusing on building strong industrial chains and enhancing local economic development through resource utilization and strategic planning [5][10]. Group 1: Resource Utilization - Liangshan has abundant wind energy resources, with the first wind farm, Dechang Wind Farm, capable of reducing carbon emissions by approximately 320,000 tons annually [7]. - The region has established a leading position in hydropower and new energy installations in Sichuan, with significant reserves of light rare earth minerals and vanadium-titanium magnetite [7]. - A resource survey initiated last year has led to substantial increases in mineral reserves, including 220 million tons of vanadium-titanium magnetite and 1.385 billion tons of phosphate rock [8]. Group 2: Industrial Chain Development - Liangshan is focusing on extending its industrial chains, exemplified by a new project for producing 125,000 tons of cathode copper, which will fill a gap in Sichuan's large-scale cathode copper production [8]. - The copper industry is projected to exceed 12 billion yuan in output this year, with plans for an integrated industrial chain encompassing mining, selection, smelting, and processing [8]. - The establishment of an AI data center project in Yanxian County aims to leverage clean energy advantages to support the digital economy, with an expected output of 2 billion yuan in the following year [8]. Group 3: Strategic Planning and Investment - Liangshan has identified over 40 target enterprises for investment, successfully signing seven projects with a total investment of 22.457 billion yuan in 2024 [10]. - The region is actively promoting a favorable business environment by providing detailed resource and energy advantages to attract enterprises [11]. - A focus on both large and small enterprises is evident, with significant collaboration between major companies like Xichang Steel and smaller firms for resource recycling and utilization [11]. Group 4: Ecological Considerations - Liangshan is committed to balancing resource development with ecological protection, implementing measures to avoid the "resource trap" often faced by resource-rich cities [13]. - The region is exploring sustainable development paths, including establishing compensation mechanisms for ecological protection in river basins [13]. - High-purity titanium production is being prioritized, with a focus on high-end applications in semiconductor manufacturing and aerospace, addressing critical supply challenges [14].