AI计算开放架构
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OpenAI:预计今年ChatGPT收入近100亿美元|首席资讯日报
首席商业评论· 2025-09-07 04:09
Group 1 - Xinba, the founder of XinXuan Group, was reported to be taken away for investigation, but the company denied the claims [2] - The film "Nanjing Photo Studio" was released in the UK, providing an opportunity for audiences to understand the history of the Nanjing Massacre [3] - The first AI computing open architecture in China was launched at the World Intelligent Industry Expo, supporting significant AI computing capabilities [4] Group 2 - Yi Huiman, during his tenure as the chairman of the China Securities Regulatory Commission, saw the A-share market breach the 3000-point mark 20 times [5][6] - OpenAI is expected to generate nearly $10 billion in revenue through ChatGPT this year, with total revenue projected to reach $13 billion [10] - A Brazilian billionaire has named football star Neymar as the sole heir to his fortune, estimated to exceed $1 billion [12]
中国首个AI计算开放架构在重庆发布
Zhong Guo Xin Wen Wang· 2025-09-05 11:22
Core Viewpoint - The launch of China's first AI computing open architecture and AI supercluster system by Zhongke Shuguang and over 20 industry chain enterprises aims to enhance collaborative innovation in AI computing, addressing computing power bottlenecks and promoting accessible computing power [1] Group 1: AI Computing Open Architecture - The AI computing open architecture is designed for large-scale intelligent computing scenarios, focusing on efficient tightly-coupled system design centered around GPUs [1] - The initiative aims to connect AI industry chain enterprises, transitioning from single-point breakthroughs in computing, storage, networking, power, cooling, management, and software to cluster innovation [1] - Zhongke Shuguang has built over 20 large-scale computing clusters in the past decade, deploying more than 500,000 heterogeneous accelerator cards [1] Group 2: AI Supercluster System - The newly launched Shuguang AI supercluster system features four main characteristics: ultra-high performance, ultra-high efficiency, ultra-high reliability, and comprehensive openness [1] - This system is designed to provide a robust computing foundation for trillion-parameter large model training and inference, industry large model fine-tuning, high-throughput inference, and multi-modal large model development [1]