Investment Rating - The report does not explicitly state an investment rating for the food and beverage industry Core Insights - The global food and beverage industry is undergoing a profound restructuring driven by technological revolution and consumer transformation, with AI technology playing a crucial role in enhancing efficiency and reshaping value across the entire supply chain [4][5][6] - The report emphasizes the need for companies in the food and beverage sector to leverage AI for transformation and upgrading, addressing challenges such as changing consumer behaviors, supply chain uncertainties, and resource constraints [4][5] Summary by Sections Industry and AI Technology Insights - The food and beverage industry is experiencing market segmentation, with consumers increasingly exhibiting cautious consumption behaviors and diverse demands [14][18] - The rise of the Y and Z generations is reshaping consumer preferences, emphasizing health, experience, and personalized products [21][27] - The integration of AI technology is essential for companies to enhance productivity, reduce costs, and adapt to evolving market dynamics [31][32] AI Transformation Case Studies - The report highlights ten typical scenarios in the food and beverage industry where AI has been successfully implemented, providing detailed case studies that illustrate demand scenarios, solutions, and outcomes [5][6][10] - Examples include supply chain management, production manufacturing, and marketing, showcasing how AI can optimize operations and enhance customer engagement [6][10] AI Transformation Practical Guide - A comprehensive guide is provided for companies to develop AI transformation strategies, focusing on strategic, execution, and organizational dimensions [7][8] - The guide emphasizes the importance of aligning internal thinking, gathering sufficient information, and fostering an AI-driven organizational evolution [7][8] Future Trends in AI Transformation - The report anticipates ongoing advancements in AI technology and its potential integration with other digital technologies, encouraging industry partners to explore and practice AI applications [5][8] - It discusses the emergence of AI agents as intelligent partners in business processes, enhancing decision-making and operational efficiency [60][64]

Industry Overview - GPU dominates the AI chip market with a 90% share in China's accelerator chip market in H1 2023, while non-GPU chips hold 10% [2] - The market size of China's accelerator chips is expected to grow from over 500,000 units in H1 2023 to over 900,000 units in H1 2024, with GPU share decreasing to 80% and non-GPU share increasing to 20% [2] - Domestic AI chip brands account for 10% of the market in H1 2023, expected to grow to 20% in H1 2024 [2] AI Chip Development - Google's TPU development timeline shows continuous advancements from TPU v1 in 2015 to TPU v5p in 2024, focusing on cost-effective inference and AI model training [4] - The evolution of TPUs has enabled large-scale training and inference capabilities, supporting AI model development [4] Data Center and Computing Power - China's data center capacity exceeds 8.3 million standard racks by June 2024, with computing power reaching 246 EFLOPS (FP32), growing at over 65% YoY [6] - Intelligent computing centers are rapidly expanding, with a focus on high power density (20-100kW per rack) and energy efficiency [5] - The AI server market in China grew from RMB 14.9 billion in 2020 to RMB 69.2 billion in 2023, projected to reach RMB 143.3 billion by 2028 [14] Cloud and AI Integration - China's cloud computing market reached RMB 616.5 billion in 2023, growing at 35.5% YoY, with expectations to reach RMB 2.14 trillion by 2027 [18] - Cloud providers are increasing AI computing power investments to meet the demands of large model training and inference [33] - AI cloud services offer advantages such as pay-as-you-go pricing, low-latency inference, and flexible resource deployment [21] Key Players and Innovations - Zhonghao Xinying, a domestic AI chip company, has developed the "Chana" TPU architecture, which outperforms international GPU chips by 1.5x in AI/ML scenarios [30] - The company's "Taize" AI computing cluster supports over 1,024 chips with high-speed interconnects, achieving performance tens of times higher than traditional GPU clusters [30] - Qingyun Technology has partnered with the National Supercomputing Center in Jinan to optimize computing resource management, achieving efficient scheduling of over 3,000P computing power [26] Market Trends and Applications - The global AI application market is booming, with downloads increasing by 26% YoY to 2.2 billion in the first eight months of 2024, and revenue growing by 51% to $2 billion [64] - AI applications are expanding across various sectors, including autonomous driving, smart cities, and industrial optimization [67] - The automotive industry is integrating AI models into vehicles, with companies like NIO, XPeng, and Li Auto developing their own AI platforms [86] Green Computing and Sustainability - China's data centers are focusing on reducing PUE (Power Usage Effectiveness) to meet national and local energy efficiency standards [90] - AI-driven energy optimization techniques are being implemented to improve resource allocation and cooling efficiency in data centers [91] - The integration of renewable energy sources and advanced cooling technologies is becoming a key focus for sustainable computing [100]

2 0 2 4 人工智能开源大模型生态研究 开源为先 场景突破 出品机构：甲子光年智库 研究指导：宋涛 报告撰写：努尔麦麦提·买合木提（小麦） 发布时间：2024.06（初版） 更新时间：2024年6月 Part 01 发展人工智能产业的重要性与新机遇 目 录 Part 02 人工智能大模型的开源生态体系分析 CONTENTS ...

Industry Overview - The AI Agent industry is at an early stage, with significant potential for growth and exploration in product and service models [14] - AI Agents are evolving from Copilot models to more autonomous systems, with 2024 being a pivotal year for this transition [14] - The distinction between Copilot and AI Agent lies in the ability for autonomous planning and execution, with AI Agents requiring minimal human intervention [15] Technological Advancements - Large Language Models (LLMs) have revolutionized AI Agents by providing enhanced understanding and generalization capabilities, enabling better handling of multiple tasks and contexts [5][6] - AI Agents are seen as an evolution of prompt engineering, with a focus on increasing autonomy and reducing human intervention [9] - Memory and planning are critical academic concepts for AI Agents, though their full potential in commercial products is yet to be realized [12] Market Dynamics - The AI Agent market is poised for a significant boom, with a shift from Copilot models to more autonomous AI Agent systems [14] - The market is currently in a state of confusion between academic and commercial concepts, with some Copilot products being considered as AI Agent models [14] - The ultimate form of AI Agents will require only initial user instructions and feedback, with no need for human intervention during the process [15] Applications and Use Cases - AI Agents can be built by ordinary individuals, making them accessible for personalized applications in the AIGC field [21] - In enterprise settings, AI Agents can collaborate with employees to enhance productivity and bring direct business value [24] - AI Agents are expected to bring about significant changes in application software forms and business models, becoming super entry points for vertical applications [36] Competitive Landscape - The AI Agent field is a crucial arena for realizing AI value, with various types of enterprises leveraging their unique strengths to enter the market [66] - Chinese AI Agent market has seen a surge in participants, including internet giants, generative AI companies, enterprise SaaS providers, startups, and 3C hardware companies [69] - The diversity of AI Agents in China is expected to further enrich, with a potential explosion in the number of enterprises [69] Key Players and Innovations - Baidu's Wenxin Intelligent Agent Platform aims to lower development barriers and provide equal opportunities for developers to create, operate, and benefit from intelligent agents [71][72] - ByteDance's Coze platform allows for rapid, low-threshold development of personal Chatbots, with integration into various channels like Doubao, Feishu, and WeChat [74][75] - Alibaba Cloud's DingTalk has launched an AI Assistant Market (AI Agent Store), significantly reducing the threshold for creation and attracting a wide range of users [79][80] Future Prospects - AI Agents are expected to become new digital productivity tools, with the combination of AIGC and workflow capabilities being key to future success [39] - The integration of AI Agents into workflows can lead to more efficient and intelligent decision-making and automation services [39] - AI Agents will play a crucial role in the accumulation and efficient reuse of enterprise knowledge assets, driving innovation in knowledge management [41]