660 AI Agents Ran 27,000 Experiments. Their Biggest Discovery Was a 2015 Textbook Result.
A recent study involving 660 AI agents conducted 27,000 experiments, claiming to develop a distributed AGI system. However, their most notable finding was a well-known technique from a 2015 textbook, Kaiming initialization, which has been widely recognized in the field of deep learning. While the underlying technology is impressive, the results do not support the claims of achieving artificial general intelligence.
- ▪The AI agents ran a total of 27,000 experiments in their research.
- ▪The biggest discovery made by the agents was Kaiming initialization, a technique established in 2015.
- ▪The infrastructure utilized in the project features advanced gradient compression and peer-to-peer networking.
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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 | DEV.to (Top) |
| Canonical URL | https://dev.to/vektor_memory_43f51a32376/660-ai-agents-ran-27000-experiments-their-biggest-discovery-was-a-2015-textbook-result-1bp2 |
| Publication time | Sun, 17 May 2026 22:07:50 +0000 |
| Retrieval time | 2026-05-17T22:33:21.086Z |
| Last seen | 2026-05-17T22:33:21.086Z |
| 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 | 3eciObbvcxBr · 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
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3862094) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Vektor Memory Posted on May 17 660 AI Agents Ran 27,000 Experiments. Their Biggest Discovery Was a 2015 Textbook Result. #ai #github #arxiv #vectordatabase On Hyperspace, basic swarms, the math nobody wrote down, and why we built the thing they were missing in a single afternoon. Join us as we traverse multiple whitepapers and agentic memory ideas like a ferret on Adderall. Some rabbit holes start with a GitHub link. Someone drops it in social posts on Facebook/Reddit/Discord.
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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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