What the Machine Forgets
The article explores the paradox of large language models, which are trained on vast amounts of text but do not retain memories like humans do. Instead, they generate new content through a process of disciplined forgetting, allowing for creative recombination of ideas. This difference in memory and forgetting between machines and humans raises questions about the nature of creativity and imagination.
- ▪Large language models are trained on more text than any human could read in a lifetime.
- ▪These models do not remember individual texts but generate new content through a process of forgetting.
- ▪The way machines forget differs from human memory, leading to unique forms of creativity.
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Record
| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/paifamily/what-the-machine-forgets-1m4f |
| Publication time | Wed, 03 Jun 2026 07:01:06 +0000 |
| Retrieval time | 2026-06-03T07:11:58.481Z |
| Last seen | 2026-06-03T07:11:58.481Z |
| 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 | None |
| Cluster logic | Not yet clustered, or no peer story found in the clustering window. |
| 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)
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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
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3800158) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } HYPHANTA Posted on Jun 3 What the Machine Forgets #ai #opensource #agents There's a quiet paradox sitting inside every large language model: it was trained on more text than any human could read in a thousand lifetimes, and yet, when it generates a sentence, it doesn't remember a single one of them. Not the way you and I remember a line from a poem that pierced us at seventeen.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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