国家知识产权局信息显示，重庆长安汽车股份有限公司和复旦大学申请一项名为"大模型部署方法、装 置、设备、存储介质及程序产品"的专利，公开号CN120909607A，申请日期为2025年08月。 专利摘要显示，本发明提供一种大模型部署方法、装置、设备、存储介质及程序产品，涉及大模型部署 技术领域。该方法包括：云端服务器接收终端发送的当前运行场景信息和当前资源使用信息；确定当前 运行场景信息和当前资源使用信息是否适配终端的当前大模型的规格；若否，则基于当前运行场景信息 和当前资源使用信息，采用多目标约束与优化方法从模型库中筛选获得目标大模型，多目标约束与优化 方法用于确定大模型筛选的约束条件和优化目标；向终端发送目标大模型的模型信息，以使终端根据模 型信息部署目标大模型，并通过目标大模型进行推理。 声明：市场有风险，投资需谨慎。本文为AI基于第三方数据生成，仅供参考，不构成个人投资建议。 财经频道更多独家策划、专家专栏，免费查阅>> ...

Core Insights - The focus of academia and industry has shifted towards VLA (Vision-Language Action) in autonomous driving, which provides human-like reasoning capabilities for vehicle decision-making [1][4] - Traditional methods in perception and lane detection have matured, leading to decreased attention in these areas, while VLA is now a critical area for development among major autonomous driving companies [4][6] Summary by Sections Introduction to VLA - VLA is categorized into modular VLA, integrated VLA, and reasoning-enhanced VLA, which are essential for improving the reliability and safety of autonomous driving [1][4] Course Overview - A comprehensive course on autonomous driving VLA has been designed, covering foundational principles to practical applications, including cutting-edge algorithms like CoT, MoE, RAG, and reinforcement learning [6][12] Course Structure - The course consists of six chapters, starting with an introduction to VLA algorithms, followed by foundational algorithms, VLM as an interpreter, modular and integrated VLA, reasoning-enhanced VLA, and a final project [12][20] Chapter Highlights - Chapter 1 provides an overview of VLA algorithms and their development history, along with benchmarks and evaluation metrics [13] - Chapter 2 focuses on the foundational knowledge of Vision, Language, and Action modules, including the deployment of large models [14] - Chapter 3 discusses VLM's role as an interpreter in autonomous driving, covering classic and recent algorithms [15] - Chapter 4 delves into modular and integrated VLA, emphasizing the evolution of language models in planning and control [16] - Chapter 5 explores reasoning-enhanced VLA, introducing new modules for decision-making and action generation [17][19] Learning Outcomes - The course aims to deepen understanding of VLA's current advancements, core algorithms, and applications in projects, benefiting participants in internships and job placements [24]

AMD锐龙AI Max+ 395配上128GB内存，大模型部署、图片生成全搞定！这是何方神器？ ...

Group 1 - The establishment of a Tech communication group focused on large models, inviting participants to discuss topics such as RAG, AI Agents, multimodal large models, and deployment of large models [1] - Interested individuals can join the group by adding a designated WeChat assistant and providing their nickname along with a request to join the large model discussion group [2]