Is AI Capable of Novelty?
AI has indeed come a long way in the last couple of years. But if we boil it down, it’s all basically just very sophisticated pattern matching. Let’s say you ask AI to write a piece of code, there’s a good chance that the data it was trained on had the exact same problem solved in many different ways. i.e. the algorithm for merge sort.But let’s say you ask it something fairly unique i.e. a specific domain modeling of your new business.
- ▪AI has indeed come a long way in the last couple of years.
- ▪But if we boil it down, it’s all basically just very sophisticated pattern matching.
- ▪Let’s say you ask AI to write a piece of code, there’s a good chance that the data it was trained on had the exact same problem solved in many different ways. i.e. the algorithm for merge sort.But let’s say you ask it something fairly uniqu
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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 | Hacker News (AI / LLM) |
| Canonical URL | https://news.ycombinator.com/item?id=49121744 |
| Publication time | Fri, 31 Jul 2026 11:20:08 +0000 |
| Retrieval time | 2026-07-31T12:12:47.142Z |
| Last seen | 2026-07-31T12:12:47.142Z |
| 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)
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
AI has indeed come a long way in the last couple of years. But if we boil it down, it’s all basically just very sophisticated pattern matching. Let’s say you ask AI to write a piece of code, there’s a good chance that the data it was trained on had the exact same problem solved in many different ways. i.e. the algorithm for merge sort.But let’s say you ask it something fairly unique i.e. a specific domain modeling of your new business. It’s quite possible that it hasn’t seen those exact requirements before but it is able to deduce your intentions from fairly close examples it’s seen before and still able to give you a well rounded answer.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Hacker News (AI / LLM).
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