华为昇腾、寒武纪宣布适配DeepSeek最新模型

Core Insights - DeepSeek officially launched the DeepSeek-V3.2-Exp model on September 29, introducing the self-developed DeepSeek Sparse Attention (DSA) mechanism, which optimizes training and inference efficiency for long texts [1][7] - The release of the new model has led to a significant reduction in service costs, with DeepSeek API prices dropping by over 50% [2][10] - The open-sourcing of the TileLang version operator has garnered considerable attention within the industry [3] Technical Innovations - The DSA mechanism is an optimization technique for the Transformer architecture, addressing the computational complexity associated with traditional dense attention mechanisms, which grow exponentially with text length [6][7] - The V3.2-Exp model has achieved substantial improvements in training and inference efficiency for long texts while maintaining performance levels comparable to the previous V3.1-Terminus model [7] Market Impact - DeepSeek has made the V3.2-Exp model fully open-source on platforms like HuggingFace and ModelScope, with related research papers also published [5] - The collaboration with domestic hardware providers such as Huawei, Cambricon, and Haiguang demonstrates the synergy between AI software and hardware ecosystems in China [11][12] - The adoption of TileLang, a programming language designed to simplify GPU operator development, is expected to enhance the efficiency of AI operator development significantly [12]