Adventures in using AI to write papers
Until recently I had only used the AI tools pay-as-you-go, but lately I have been experimenting with the $20 monthly subscription. I would periodically just set the AI tools on writing papers I have wanted to write for quite some time. It was motivated by a paper from Kim Rossmo on likely locations of a lost hiker based on cell tower pings and hypothetically using a drone to search Joshua Tree for that hiker.
- ▪Until recently I had only used the AI tools pay-as-you-go, but lately I have been experimenting with the $20 monthly subscription.
- ▪I would periodically just set the AI tools on writing papers I have wanted to write for quite some time.
- ▪It was motivated by a paper from Kim Rossmo on likely locations of a lost hiker based on cell tower pings and hypothetically using a drone to search Joshua Tree for that hiker.
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Record
| Original publisher | Andrew Wheeler |
| Canonical URL | https://andrewpwheeler.com/2026/09/24/adventures-in-using-ai-to-write-papers/ |
| Publication time | Thu, 24 Sep 2026 15:19:23 +0000 |
| Retrieval time | 2026-09-24T15:25:26.692Z |
| Last seen | 2026-09-24T15:25:26.692Z |
| 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 | A8AmFHlnvJEr · 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 |
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
Until recently I had only used the AI tools pay-as-you-go, but lately I have been experimenting with the $20 monthly subscription. So I ended up with extra credits to burn. I would periodically just set the AI tools on writing papers I have wanted to write for quite some time. Here are some of those experiments. Of these, the Crime Decomposition paper is the only one I spent more than a day on. (And that was mostly because it was running models that originally took 10+ hours and then would fail, until I had it switch the model to one that was much faster.) Optimal Search Paths – this is a project around drawing optimal search paths when you have a smooth surface where an object is likely to be found.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Andrew Wheeler.
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