**新一代序列建模架构Mamba-2正式发布，训练效率大幅提升**
近日，新一代序列建模架构Mamba-2正式发布，并成功入选ICML 2024。该架构由资深科研人员Albert Gu和Tri Dao共同研发，将Transformer和状态空间模型（SSM）两大主流序列建模技术融为一体。
Mamba-2通过引入结构化状态空间二元性（SSD）理论框架，创新地解决了序列建模的难题。新架构的状态空间扩大了8倍，而训练速度则提升了50%，标志着人工智能领域的一大突破。值得一提的是，该架构在参数规模为3B时，在300B tokens的训练中表现超越了之前的Mamba-1以及同等规模的Transformer，特别是在需要更大状态容量的任务上显示了显著改进。
该成果不仅是技术上的飞跃，也为人工智能领域未来的发展打开了新的大门。Mamba-2的发布预示着序列建模技术的进一步成熟，未来或将在自然语言处理、图像识别等领域发挥更大的作用。随着研究的深入和技术的普及，我们有理由期待这一架构在推动AI技术革新方面发挥更加重要的作用。
上述成果的发布获得了业内的广泛关注与高度评价，标志着人工智能领域又迈出了重要的一步。
英语如下：
News Title: “Mamba-2 Architecture Launched: Training Efficiency Soars, Unifying Transformer and SSM”
Keywords: Mamba 2 launch, improved training efficiency, architectural innovation
News Content: **New Generation Sequence Modeling Architecture Mamba-2 Officially Released, with Significant Training Efficiency Boost**
Recently, the new generation sequence modeling architecture Mamba-2 was officially released and successfully selected for ICML 2024. Jointly developed by senior researchers Albert Gu and Tri Dao, this architecture integrates the two major sequence modeling technologies of Transformer and State Space Model (SSM).
Mamba-2 innovatively solves the problem of sequence modeling by introducing the Structured State Space Duality (SSD) theoretical framework. The new architecture expands the state space by eight times while increasing training speed by 50%, marking a major breakthrough in the field of artificial intelligence. Notably, when the parameter size is 3B, it outperforms the previous Mamba-1 and Transformer of the same scale in training with 300B tokens, particularly showing significant improvements in tasks that require larger state capacity.
This achievement is not only a technological leap, but also opens a new door for the future development of artificial intelligence. The release of Mamba-2 indicates the further maturity of sequence modeling technology, and it is expected to play a greater role in natural language processing, image recognition, and other fields in the future. With the deepening of research and the popularization of technology, we have reason to expect this architecture to play an increasingly important role in driving innovation in AI technology.
The release of these achievements has received widespread attention and high praise from the industry, marking another important step in the field of artificial intelligence.
【来源】https://ai-bot.cn/go/?url=aHR0cHM6Ly93d3cucWJpdGFpLmNvbS8yMDI0LzA2LzE0OTg5My5odG1s
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