Echoform – unlimited LLM memory via a single 64 KB hypervector
ECHOFORM introduces a novel memory substrate for AI agents, allowing for effectively unlimited long-term memory without consuming context tokens. It utilizes a single 64 KB hypervector to store agent history and provides cryptographic verification for memory retention and deletion. This system is designed to comply with GDPR regulations, offering a proof of data erasure.
- ▪ECHOFORM stores agent history as a single side-channel FHRR hypervector, avoiding the need for context tokens or model weight updates.
- ▪Every recall includes a signed forgetting certificate, providing verifiable proof of what data is retained or deleted.
- ▪The system is model-agnostic and compatible with various AI models, including Llama-3.1 and GPT.
Hacker News (AI / LLM) files mainly under ai. We currently carry 3,301 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/OpenAgentic-Labs/echoform-ghost-memory |
| Publication time | Tue, 19 May 2026 13:18:48 +0000 |
| Retrieval time | 2026-05-19T13:29:57.664Z |
| Last seen | 2026-05-19T13:29:57.664Z |
| 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 | EdEX77jwhQmV |
| 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 |
Rights status (four layers)
WeSearch handling by dimension
| 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
ECHOFORM Ghost Memory Effectively unlimited long-term memory for any LLM — zero context tokens · zero weight updates · cryptographic forgetting curve. Install · How it works · API · Cloud deploy · Architecture · Provenance If ECHOFORM saves you a context window — drop a ⭐ on the repo. Stars are the only signal that tells us to keep shipping. It takes one click. What is this? ECHOFORM is a production memory substrate for AI agents. Existing systems (Mem0, Zep, Letta, …) treat memory as a retrieval problem — fetch chunks, stuff them back into the prompt, watch the bill scale with episode count.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.