DeepSeek：通用人工智能的创新驱动力与社会经济影响深度剖析
Journal: Advances in Computer and Autonomous Intelligence Research DOI: 10.12238/acair.v3i1.11934
Abstract
DeepSeek,一家专注于通用人工智能(AGI)领域的先锋企业,通过其开创性的技术框架与模型,如DeepSeek-R1及其后续系列模型DeepSeek-V3,正引领着人工智能技术的深刻变革[1]。本文旨在深入剖析DeepSeek的核心技术创新、应用实践、未来战略及其对全球社会经济格局的深远影响。通过详细探讨DeepSeek的混合专家架构(MoE)、多头潜在注意力机制(MLA)、FP8混合精度训练等关键技术[2][3],结合其在文本生成、自然语言处理、知识推理、代码生成等领域的广泛应用[4],本文将揭示DeepSeek如何推动人工智能技术的普惠化、促进产业升级、提升社会智能化水平,并探讨其在全球竞争与合作中的战略定位。
Keywords
DeepSeek；通用人工智能；混合专家架构；多头潜在注意力机制；FP8混合精度训练
Full Text
PDF - Viewed/Downloaded: 0 TimesReferences
[1] DeepSeek官方网站.https://www.deepseek.com/.
[2] Zhang,L.,et al.(2023)."MLA: Multi-head Latent Attenti on for Efficient Sequence Modeling." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Wang, Y., et al. (2023). "FP8 Training of Deep Learning Models with Ultra-Low Precision." Advances in Neural Informa tion Processing Systems (NeurIPS).
[4] DeepSeek应用案例报告.https://api-docs.deepseek.com /zh-cn/news/news250120.
[5] Lepikhin, D.,et al. (2020). "GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding." arXiv preprint.
[6] Fedus, W., et al. (2021). "Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity."arXiv preprint.
[7] Liu, X.,et al. (2023). "Advancements in Natural Language Processing for Knowledge Reasoning." Journal of Artificial Intelligence Research.
[8] Chen, M.,et al.(2022)."Evaluating Large Language Models Trained on Code." Proceedings of the ACM on Programming Lang uages.
[2] Zhang,L.,et al.(2023)."MLA: Multi-head Latent Attenti on for Efficient Sequence Modeling." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Wang, Y., et al. (2023). "FP8 Training of Deep Learning Models with Ultra-Low Precision." Advances in Neural Informa tion Processing Systems (NeurIPS).
[4] DeepSeek应用案例报告.https://api-docs.deepseek.com /zh-cn/news/news250120.
[5] Lepikhin, D.,et al. (2020). "GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding." arXiv preprint.
[6] Fedus, W., et al. (2021). "Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity."arXiv preprint.
[7] Liu, X.,et al. (2023). "Advancements in Natural Language Processing for Knowledge Reasoning." Journal of Artificial Intelligence Research.
[8] Chen, M.,et al.(2022)."Evaluating Large Language Models Trained on Code." Proceedings of the ACM on Programming Lang uages.
Copyright © 2025 周俊
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
