【环球网科技综合报道】随着人工智能技术加速渗透，大模型应用已从"能不能用"的探索期，迈入"如何长期、稳定、规模化运行"的深水区，模型API服务 的真实表现、稳定性与调用效率成为产业关注的核心议题。1月29日，"Ping The Future：智能跃迁，路由新境——清程AI Ping产品发布会"在北京举行。来 自政府部门、科研机构、云服务平台、大模型服务商及应用企业的多方代表，围绕大模型 API 服务的评测体系、工程化使用与生态协同展开深入交流。 清华大学教授郑纬民认为，人工智能基础设施的核心任务已发生关键转变。过去，AI Infra聚焦大模型训练与推理，解决"如何生产智能"的问题；如今随着 模型生态丰富和智能体广泛应用，行业进入以"智能流通"为核心的新阶段，更关注模型能力在真实业务中的高效稳定应用。在他看来，实现智能流通的关键 在于构建"模型路由"与"服务路由"协同的智能路由能力，前者可在多模型环境下为不同任务匹配最优模型，后者能在同一模型的多API服务提供者间优化调 度性能与成本，二者结合将形成完整的AI任务分发网络，决定人工智能系统的最终效率与使用成本。 随着大模型API服务在政务、金融、工业与消费等多元 ...

中证报中证网讯(记者孟培嘉)清程极智1月29日发布AI Ping平台。据介绍，AI Ping聚焦大模型服务使用 环节，围绕模型服务评测、统一接入与智能路由等核心能力，构建起覆盖"评测—接入—路由—优化"的 完整链路。平台以真实业务场景为导向，对不同厂商、不同模型API的延迟、稳定性、吞吐与性价比等 关键指标进行长期、持续观测。目前，AI Ping已覆盖30余家国内大模型API服务商，在统一标准与方法 论下对模型服务能力进行对比分析，为企业在复杂的模型与服务选择中提供更加理性的决策参考。 清华大学教授郑纬民在发布会上表示，当前人工智能基础设施的核心任务正在发生变化。过去，AI Infra主要服务于大模型的训练与推理，解决"如何生产智能"的问题；随着模型生态不断丰富和智能体广 泛应用，行业正在进入以"智能流通"为核心的新阶段，更加关注模型能力如何在真实业务中高效、稳定 地被使用。实现智能流通的关键在于智能路由能力建设，其中既包括在多模型环境下为不同任务选择最 合适模型的"模型路由"，也包括在同一模型的多种API服务提供者之间进行性能与成本优化调度的"服务 路由"。两类路由能力协同发展，将形成完整的AI任务分发网络 ...

Core Insights - The company, Pingao Co., Ltd. (688227.SH), has disclosed its technological advancements in the AI sector, focusing on software and algorithm optimization to reduce reliance on high-performance hardware, particularly in the context of overseas high-end chip bans [1] - The trend in the industry indicates that AI software capabilities are improving, leading to lower hardware performance requirements, as modern AI algorithms show increased tolerance for hardware errors and noise [2] - Pingao's approach combines domestic chips with software optimization, allowing less powerful domestic chips to achieve higher performance through innovative software solutions [3] Industry Trends - The industry consensus is shifting towards software optimization to enhance the efficiency of domestic chips, with various domestic enterprises and research institutions investing in this direction [2] - Notable advancements include Tsinghua University's "Bagua Furnace" training system and "Chitu" inference engine, which optimize the efficiency of domestic computing power [2] Company Solutions - Pingao's "Pingyuan AI All-in-One Machine," developed in collaboration with Jiangyuan Technology, exemplifies the company's strategy, achieving a 30% increase in response speed for the DeepSeek-R1 model and a 2.5 times improvement in energy efficiency compared to mainstream GPUs [3] - The company has developed the BingoAIInfra intelligent computing power scheduling platform, which enhances the utilization of domestic hardware by allowing precise management of GPU resources [4] Ecosystem Layout - Pingao is building a comprehensive "hardware-software-ecosystem" system to ensure the sustainable development of its technology, including strategic investments in domestic chip companies and collaboration on optimizing inference algorithms [5] - The company’s Pingao Cloud operating system supports a wide range of domestic heterogeneous chip servers and applications, creating a self-controlled ecosystem that mitigates risks associated with overseas technology limitations [5] Conclusion - In the context of rapid digital economy and AI industry growth, Pingao's innovative approach not only achieves technological breakthroughs but also provides a viable path for mainstream AI applications to transition from reliance on overseas high-end hardware to domestic chips, thereby driving the autonomous development of domestic AI computing power [6]