| 纂]項下的圖纂 數目 | [编纂]股H股(視乎[编纂]行使與否而定) | | --- | --- | | [编纂]數目 | [编纂]股H股(可予重新分配) | | [编纂]數目 | [編纂]股H股(可予重新分配及視乎[編纂] | | 行使與否而定) | | | 最高 编纂] | 每股H股[編纂]港元,另加1.0%經紀佣金、0.0027% | | | 證監會交易徵費、0.00565%聯交所交易費及 | | | 0.00015%會財局交易徵費(須於申請時以港元繳 | | 足,多繳股款可予退還) | | | 面值 | 每股H股人民幣[0.10]元 | | [編纂] | [編纂] | | CICC中金公司 | 獨家保薦人、 编纂] 编纂] | 2025年12月19日，来自北京海淀区的北京智谱华章科技股份有限公司Knowledge Atlas Technology Joint Stock Company Limited.(以下简 称"智谱")在港交所披露聆讯后的招股书，或很快在香港主板IPO上市。 智谱华章招股书链接： 主要业务 智谱 ，成立于2019年，作为中国领先的人工智能公司，追求通用人工智能( AGI) 创 ...

Group 1 - The 2025 World Artificial Intelligence Conference (WAIC) showcased a shift from homogeneous competition among large model vendors to differentiated strategies, with companies focusing on long text processing, multimodal capabilities, and vertical scene development [2] - The boundaries between models and applications are becoming increasingly blurred, with leading vendors transitioning from pure model providers to comprehensive platforms that integrate generation, retrieval, and tool invocation capabilities [2] - The industry is exploring a hybrid model of open-source and closed-source, with some companies like OpenAI and Zhipu releasing open-source models, while others like Meta are developing advanced closed-source products [2] Group 2 - Internet cloud vendors are building model-centric full-stack capabilities, offering "Model as a Service" (MaaS) platforms that may change the logic of enterprises moving to the cloud, especially for small and medium-sized enterprises facing challenges with private AI cloud setups [3] - The progress of domestic computing power is highlighted by Huawei's Ascend 384 super node cluster, which boasts double the computing power of NVIDIA's GB200 NVL72 system, although domestic GPUs still lag in key inference performance metrics [4] - The demand for private deployment is reflected in the popularity of AI integrated machines, with domestic GPU manufacturers seeking breakthroughs through collaborative innovation [4] Group 3 - Despite high interest in smart robots and AR glasses, edge AI is still in a preparatory stage, facing challenges in multimodal perception, interaction, and autonomous decision-making capabilities [5] - The smartphone is seen as a potential primary carrier for AI agents due to its advantages in computing power, interaction, and application scenarios, with a cautious approach from manufacturers indicating the need for further technological maturity [5] - Continuous investment in the industry chain is laying the groundwork for future developments in edge AI, suggesting a positive outlook despite the current limitations [5]