Ask HN: Do you hide your AI behind a curtain?
I used AI to build a music recommender system that itself uses no AI in its operation.I have been promoting the system in communities that can sometimes be considerably anti-AI. But people usually assume that it is AI because, well, it's a recommender system.Anyways, after a 30-year break, I rebuilt it and got it working the way I always wanted! It basically uses the same 10 lines of code, (for which I was granted now-expired US patent #5749081), but with a good interface around it instead of a lousy 1990s one.You tell it your 5 favorite albums, and it recommends other albums to try.It uses collaborative filtering (CF) to generate the music recommendations.
- ▪I used AI to build a music recommender system that itself uses no AI in its operation.I have been promoting the system in communities that can sometimes be considerably anti-AI.
- ▪But people usually assume that it is AI because, well, it's a recommender system.Anyways, after a 30-year break, I rebuilt it and got it working the way I always wanted!
- ▪It basically uses the same 10 lines of code, (for which I was granted now-expired US patent #5749081), but with a good interface around it instead of a lousy 1990s one.You tell it your 5 favorite albums, and it recommends other albums to tr
2 outlets in our directory ran this story. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
- ▪ Do you hide your AI behind a curtain? — Similaritiesengine
Hacker News (AI / LLM) files mainly under ai. We currently carry 2,495 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
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 | Ycombinator |
| Canonical URL | https://news.ycombinator.com/item?id=49074416 |
| Publication time | Mon, 27 Jul 2026 19:20:45 +0000 |
| Retrieval time | 2026-07-27T19:29:48.774Z |
| Last seen | 2026-07-27T19:29:48.774Z |
| 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 | xNfLwGgHvavL · 2 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 |
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
I used AI to build a music recommender system that itself uses no AI in its operation.I have been promoting the system in communities that can sometimes be considerably anti-AI. But people usually assume that it is AI because, well, it's a recommender system.Anyways, after a 30-year break, I rebuilt it and got it working the way I always wanted! It basically uses the same 10 lines of code, (for which I was granted now-expired US patent #5749081), but with a good interface around it instead of a lousy 1990s one.You tell it your 5 favorite albums, and it recommends other albums to try.It uses collaborative filtering (CF) to generate the music recommendations.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Ycombinator.