Asked AI to do a mini math breakthrough. It did a mini breakthrough
AI Refines AI A reproducible candidate improvement to the 67.25% zeta-zero bound. One AI system produced Anthropic's new Theorem D. A second AI-generated research draft found a small strengthening.
- ▪AI Refines AI A reproducible candidate improvement to the 67.25% zeta-zero bound.
- ▪One AI system produced Anthropic's new Theorem D.
- ▪A second AI-generated research draft found a small strengthening.
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| Original publisher | GitHub |
| Canonical URL | https://github.com/learademacher/ai-refines-ai-zeta-bound |
| Publication time | Tue, 11 Aug 2026 21:17:08 +0000 |
| Retrieval time | 2026-08-11T21:20:44.316Z |
| Last seen | 2026-08-11T21:20:44.316Z |
| 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 | VmZmFHyO00cd · 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 |
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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
AI Refines AI A reproducible candidate improvement to the 67.25% zeta-zero bound. One AI system produced Anthropic's new Theorem D. A second AI-generated research draft found a small strengthening. This repository packages the stronger argument, its exact interval-arithmetic verifier, and a clean-room reproduction of the only computer-assisted lemma. The candidate bound is $$ \liminf_{T\to\infty}\frac{N_0^s(T,2T)}{N(T,2T)} \ge 0.6730213619501665335\ldots. $$ Here $N(T,2T)$ counts nontrivial zeros with multiplicity, while $N_0^s(T,2T)$ counts simple zeros on the critical line. ImportantThis is an unreviewed candidate refinement. It does not prove the Riemann hypothesis and it does not independently replace the analytic results imported from Anthropic's Theorem D.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.