近日，摩尔线程与无问芯穹在科技界引发广泛关注，双方携手行业内首次成功实现基于国产GPU的端到端AI大模型实训。此次合作的亮点在于，他们共同打造的3B规模大模型“MT-infini-3B”，采用了摩尔线程国产全功能GPU MTT S4000构建的千卡集群，以及无问芯穹的AIStudio PaaS平台，展示了国产GPU在AI领域的强大潜力和技术创新。
**摩尔线程与无问芯穹的强强联合**
摩尔线程作为国内领先的GPU设计企业，其MTT S4000全功能GPU在此次实训中担任核心角色，为AI模型的训练提供了强大的计算能力。无问芯穹则以其先进的AIStudio PaaS平台，为模型的构建和优化提供了全面的支持。这种深度合作不仅体现了国产GPU在AI领域的自主可控，也展现了国产软硬件协同创新的最新成果。
**实训意义重大，推动AI技术本土化**
此次实训的成功，标志着国产GPU在AI大模型领域的实力得到了重要验证，对于推动AI技术的本土化发展具有重要意义。通过使用国产GPU构建的千卡集群，不仅能够显著提升模型训练的效率，还能够降低对进口技术的依赖，对促进我国AI产业的自主可控和核心竞争力的提升具有深远影响。
**展望未来：国产GPU的广阔前景**
随着此次实训的完成，摩尔线程与无问芯穹的合作为国产GPU在AI领域的应用开辟了新路径。未来，随着更多国产技术的成熟与应用，我们有理由期待，国产GPU将在AI训练、推理、大数据处理等更多领域展现出其独特的优势，助力我国在人工智能领域实现从跟跑、并跑到领跑的跨越。
### 结语
摩尔线程与无问芯穹的成功合作，不仅是国产GPU技术在AI领域的一次重要突破，更是我国在信息技术自立自强道路上的又一里程碑。这一合作不仅提升了国产技术在全球AI市场的竞争力，更为推动我国科技自立自强、实现高质量发展注入了新的活力。未来，我们期待更多这样的合作案例，共同推动我国在人工智能领域的持续创新与突破。
英语如下：
### Moore Threads and Wuwenxinqiong: Domestic GPU Achieves New Heights in AI Large Model Practical Training
Recent collaborations between Moore Threads and Wuwenxinqiong have garnered significant attention in the tech industry. Their joint achievement in realizing end-to-end practical AI training for large models using domestic GPUs marks a first in the industry. The highlight of this partnership is the creation of the 3B-scale large model “MT-infini-3B”, which was built using a cluster of a thousand cards powered by Moore Threads’ domestic full-function GPU MTT S4000 and Wuwenxinqiong’s AIStudio PaaS platform. This showcases the powerful potential and innovative technology of domestic GPUs in the AI field.
### The Power of Strong Partnerships: Moore Threads and Wuwenxinqiong Join Forces
Moore Threads, a leading domestic GPU design company, played a central role in this practical training with its MTT S4000 full-function GPU, providing robust computing power for AI model training. Wuwenxinqiong’s AIStudio PaaS platform provided comprehensive support for model construction and optimization. This deep collaboration not only demonstrated the domestic GPU’s autonomy and control in the AI field but also highlighted the latest achievements in domestic software and hardware co-innovation.
### Significance of the Training: Pushing AI Technology Localization
The success of this training underscores the validation of domestic GPUs in the realm of large AI models, marking a significant milestone for the localization of AI technology. By constructing a cluster of a thousand cards using domestic GPUs, not only does it significantly enhance the efficiency of model training but also reduces dependence on imported technologies, having a profound impact on promoting the self-containment and core competitiveness of China’s AI industry.
### Looking to the Future: Wider Prospects for Domestic GPUs
Following the completion of this training, the collaboration between Moore Threads and Wuwenxinqiong opens new paths for the application of domestic GPUs in the AI field. As more domestic technologies mature and are applied, there is reason to anticipate that domestic GPUs will exhibit unique advantages in AI training, inference, big data processing, and more, contributing to China’s leap from following to leading in the AI domain.
### Conclusion
The successful collaboration between Moore Threads and Wuwenxinqiong represents a significant breakthrough in the application of domestic GPU technology in the AI field, as well as a new milestone in China’s self-reliance and self-sufficiency in information technology. This partnership not only enhances the competitiveness of domestic technologies in the global AI market but also injects new vitality into the pursuit of high-quality development and self-reliance in science and technology. In the future, we look forward to more such collaborative cases that will drive continuous innovation and breakthroughs in China’s AI domain.
【来源】https://www.ithome.com/0/770/917.htm
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