LLM memory doesn't only get written wrong, it goes wrong later
A project is underway to develop a memory system for long-running conversations with a language model, focusing on the issue of facts becoming outdated over time. The system, called ANAMNESIS, is designed to organize memory in four tiers and ensure that nothing enters semantic memory unexamined. The project aims to address the gap in current systems, which do not forecast which memories will become outdated and do not have a repair loop to update them.
- ▪The ANAMNESIS project is developing a local-first memory system for long-running conversations with a language model.
- ▪The system is designed to organize memory in four tiers, loosely mapped to how cognitive neuroscience decomposes human long-term memory.
- ▪Current memory systems do not forecast which memories will become outdated and do not have a repair loop to update them.
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| Original publisher | Hacker News (AI / LLM) |
| Canonical URL | https://manazir.dev/work/anamnesis-forecasting-memory-corruption |
| Publication time | Tue, 04 Aug 2026 05:30:59 +0000 |
| Retrieval time | 2026-08-04T05:35:45.751Z |
| Last seen | 2026-08-04T05:35:45.751Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | oUUhFwzkhzBT · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
August 3, 2026A living documentThis is not a finished paper. It is the working record of a final-year project that runs to April 2027, and I update it as the work moves rather than writing it once at the end. Section 8 is the changelog, and the status table below is the fastest way to see what is actually true today.Two disciplines carry over from the thesis into this page. Nothing is claimed as a result until it has been measured, and anything still pending says so in plain words. Where the work has already proved me wrong, that is on the page too, because those are the parts worth reading.1. The problemA memory system reads your conversation and distils it into short facts it can recall later.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Hacker News (AI / LLM).