DeepSeek AI's Engram: A Novel Memory Axis for Sparse LLMs
Published:Jan 15, 2026 07:54
•1 min read
•MarkTechPost
Analysis
DeepSeek's Engram module addresses a critical efficiency bottleneck in large language models by introducing a conditional memory axis. This approach promises to improve performance and reduce computational cost by allowing LLMs to efficiently lookup and reuse knowledge, instead of repeatedly recomputing patterns.
Key Takeaways
Reference
“DeepSeek’s new Engram module targets exactly this gap by adding a conditional memory axis that works alongside MoE rather than replacing it.”