Unverified50% confidenceOpinionExact time
According to analysis by Bilibili UP host '1024 Engineering Notes,' DeepSeek's Harness deliberately leaves the memory functionality blank, leaving that space for the community.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/27/2026
First Seen
Valid until: 12/26/2026
Sources
Related Entities
Related Claims
UnverifiedThe project has a built-in experimental VRAM offloading mechanism (demonstrated in workflow 06) that can significantly reduce memory usage, but memory spikes still occur during the process.65% similarVerifiedMainstream strategies for addressing short-term memory limitations include sliding window truncation, summary compression, and importance-based selective retention, with each strategy striking a different balance between information completeness and token consumption.63% similarUnverifiedBecause the agent itself evaluates whether a memory is useful, Slowave no longer needs a separate LLM judge to maintain memories, thereby avoiding token waste and the split-brain problem.61% similarUnverifiedActive forgetting and summary compression are necessary measures to combat the unbounded growth of memory stores.60% similarVerifiedMulti-Head Latent Attention (MLA) significantly reduces KV Cache memory usage during the inference phase by performing low-rank compression on the Key-Value cache.60% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/954604API
curl https://kongchang.com/api/v1/knowledge/claims/954604MCP
get_claim(id=954604)