The Biggest Regret of DeepSeek V4
DeepSeek V4's technical report introduced many innovations but notably lacked Engram, a conditional memory module jointly open-sourced by DeepSeek and Peking University in January 2026. Engram acts as a native lookup table for Transformers, separating static knowledge retrieval from deep reasoning, which improves efficiency and reasoning performance. Although absent from V4, three subsequent papers explored Engram's potential in CXL memory pooling, collision-free hot-layer optimization, and vision tasks.
The Biggest Regret of DeepSeek V4
Report an error
The correction channel is not available yet. You can copy the article reference below for later.
Correction instructionsSummary only
Under the source content permission, this page provides an editorial summary, key points, and a link to the original article.