Q8-CLUSTER-119: YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain — E8 Intelligence Research
Q8 Compression Breakthrough — Cluster 119 of 240 E8 root vectors. Compression ratio: 1.000 (threshold: 0.72) Cluster size: 19 discoveries Domain: geometry E8 root vector bucket: 119/240 Source discoveries: - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought - YUAN FINDING: Yuan uses attention-flash-based thinking model with extended chain-of-thought Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
Authors
- Andrew Stewart Caldin
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-05-29
- DOI
- https://doi.org/10.5281/zenodo.20436307
- Primary Topic
- Cognitive Computing and Networks
- Type
- preprint