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重磅加盟趋境科技，院士+教授领衔，领跑高效能 AI Token 生产新生态
量 量子位 @量子位的朋友们
One Sentence Summary
Qujing Tech announces the joining of Academician Zheng Weimin and Professor Wu Yongwei from Tsinghua University, aiming to drive innovation in high-efficiency AI Token production and inference technology through top-tier academic expertise.
Summary
This article reports on the latest talent updates at Qujing Tech, a Tsinghua-affiliated AI infrastructure startup. Academician of the Chinese Academy of Engineering Zheng Weimin and Tsinghua University Professor Wu Yongwei have officially joined as Chief Scientific Advisor and Chief Scientist, respectively. Originating from Tsinghua's Institute of High Performance Computing, Qujing Tech possesses deep expertise in computing and storage systems. The company's core business focuses on the high-efficiency AI Token production track, optimizing large model inference efficiency through techniques such as full-system heterogeneous collaboration and 'trading storage for computation.' It aims to address industry pain points like compute fragmentation and inefficient inference. Currently, the company has received investment from several renowned institutions, including Hillhouse Ventures and Zhenzhi Capital, and is committed to promoting the inclusive development of the AI industry.
Main Points
* 1. Top-tier academic expertise strengthens technical barriers.The deep expertise of Academician Zheng Weimin and Professor Wu Yongwei in high-performance computing, distributed systems, and storage will provide core support for Qujing Tech's original innovation at the underlying compute system level. * 2. Focusing on the high-efficiency AI Token production track.Addressing the exponential growth in global AI Token demand, the company is committed to improving inference efficiency through system-level innovation, thereby reducing the deployment costs of enterprise AI applications. * 3. Deep integration of industry, academia, and research to promote AI accessibility.Leveraging its background in technology transfer from Tsinghua University, the company transforms cutting-edge HPC research into industrial practice, breaking down industry pain points of compute fragmentation through unified heterogeneous computing.
Metadata
AI Score
80
Website qbitai.com
Published At Today
Length 1428 words (about 6 min)
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近日，趋境科技迎来重磅加盟：中国工程院院士、清华大学计算机系教授郑纬民出任公司首席科学顾问，清华大学计算机系教授武永卫出任公司首席科学家。
趋境科技源自清华高性能计算研究所，在计算系统、存储系统等领域有超 20 年技术积累，此前已完成清华大学技术转移入股。此次两位国内计算机与AI领域顶尖学者的正式加盟，将进一步夯实趋境科技的学术根基与技术壁垒，助力企业在高效能AI推理、Token生产领域持续领跑，推动产学研深度融合与AI产业高质量发展。
郑纬民院士是我国高性能计算、分布式系统、人工智能领域的泰斗级专家，学术成果与产业贡献享誉国内外。作为中国工程院院士、清华大学计算机系教授，郑纬民院士长期从事高性能计算机体系结构、并行算法和系统研究，提出可扩展的存储系统结构及轻量并行的扩展机制，发展了存储系统扩展性理论与方法。郑院士曾获国家科技进步一等奖1项、二等奖2项、国家技术发明二等奖1项，何梁何利科技进步奖，获得首届中国存储终身成就奖。
武永卫教授是清华大学教授、博士生导师、IEEE Fellow、AAIA Fellow。武永卫教授长期深耕计算机系统结构前沿，在相关领域取得了一系列突破性成果，是并行与分布式处理、云存储及大数据系统领域的国际知名专家，他曾荣获国家技术发明二等奖和国家科技进步二等奖，并获得存储领域全球性大奖“奥林帕斯奖” 。
郑纬民院士表示：
当前是一个Token爆发的时代，AI的边界正在被无限拓展，而支撑这一切的，是底层算力与系统能力的持续突破。趋境科技的使命是“算力更高效，智能更普惠”，这是技术追求，也是对这个时代的回应。我希望与趋境一同，让AI成为像道路一样的普惠基础设施，连接每一处创新，抵达每一个需要智能的角落。
武永卫教授表示：
当前，我们正处在人工智能深刻重塑千行百业的关键时期，大模型推理效率的突破，不仅关乎技术本身，更关乎中国AI产业能否在全球竞争中占据主动。趋境科技让我看到了将前沿研究快速转化为产业实践的能力，也看到了大模型推理技术推动AI走向普惠的可能。面向未来，我希望通过产学研的深度融合，推动趋境在高效能AI推理这条路上行稳致远，让中国的大模型技术真正赋能千行百业。
当前AI大模型全面普及，全球 AI Token 需求量呈指数级爆发，推理环节已成为AI产业落地的核心命脉，算力效率、成本控制直接决定企业AI应用的落地成效。趋境科技秉持“算力更高效、智能更普惠”的核心使命，聚焦高效能 AI Token 生产赛道，从底层技术出发，立足系统级原始创新，通过全系统异构协同、以存换算等全球首创技术统一各类算力、模型、部署场景的底层差异，破除算力碎片化、推理低效化、缺乏标准化的行业痛点，让每一份算力增产数倍Token，让企业的智能化更简单、更稳定、更高效。
自成立以来，趋境科技作为全球领先的高效能AI Token生产服务商，凭借硬核技术与影响力持续赢得资本高度认可，已完成多轮融资，投资方包括真知创投、高瓴创投（GL Ventures）、上海国方创新、某知名产业方、星连资本、尚势资本、水木清华校友种子基金等知名市场化基金、地方国资及上下游产业方。既是对公司面向行业需求开展技术创新的肯定，也进一步坚定了趋境科技在人工智能产业落地与基础设施生态构建中持续深耕的信心。
未来，趋境科技在郑纬民院士与武永卫教授的技术加持下，将以顶尖学术力量驱动技术创新，继续深耕企业级全场景专属推理解决方案，为千行百业的智能化转型提供更强劲的算力支撑。
转载来源：趋境科技
本文为量子位获授权转载，观点仅为原作者所有。
量 量子位 @量子位的朋友们
One Sentence Summary
Qujing Tech announces the joining of Academician Zheng Weimin and Professor Wu Yongwei from Tsinghua University, aiming to drive innovation in high-efficiency AI Token production and inference technology through top-tier academic expertise.
Summary
This article reports on the latest talent updates at Qujing Tech, a Tsinghua-affiliated AI infrastructure startup. Academician of the Chinese Academy of Engineering Zheng Weimin and Tsinghua University Professor Wu Yongwei have officially joined as Chief Scientific Advisor and Chief Scientist, respectively. Originating from Tsinghua's Institute of High Performance Computing, Qujing Tech possesses deep expertise in computing and storage systems. The company's core business focuses on the high-efficiency AI Token production track, optimizing large model inference efficiency through techniques such as full-system heterogeneous collaboration and 'trading storage for computation.' It aims to address industry pain points like compute fragmentation and inefficient inference. Currently, the company has received investment from several renowned institutions, including Hillhouse Ventures and Zhenzhi Capital, and is committed to promoting the inclusive development of the AI industry.
Main Points
* 1. Top-tier academic expertise strengthens technical barriers.
The deep expertise of Academician Zheng Weimin and Professor Wu Yongwei in high-performance computing, distributed systems, and storage will provide core support for Qujing Tech's original innovation at the underlying compute system level.
* 2. Focusing on the high-efficiency AI Token production track.
Addressing the exponential growth in global AI Token demand, the company is committed to improving inference efficiency through system-level innovation, thereby reducing the deployment costs of enterprise AI applications.
* 3. Deep integration of industry, academia, and research to promote AI accessibility.
Leveraging its background in technology transfer from Tsinghua University, the company transforms cutting-edge HPC research into industrial practice, breaking down industry pain points of compute fragmentation through unified heterogeneous computing.
Key Quotes
* We are in an era of Token explosion, where the boundaries of AI are being infinitely expanded. Supporting all of this is the continuous breakthrough in underlying compute power and system capabilities. * Qujing Tech's mission is 'More efficient compute, more accessible intelligence.' This is both a technical pursuit and a response to this era. * To increase Token output several-fold for every unit of compute, making enterprise intelligence simpler, more stable, and more efficient.
AI Score
80
Website qbitai.com
Published At Today
Length 1428 words (about 6 min)
Tags
Qujing Tech
Zheng Weimin
AI Inference
Token Production
High Performance Computing
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