Red queen hypothesis – A new way forward for self-improving AI
hardlianotion
36 points
4 comments
August 16, 2026
Related Discussions
Found 5 related stories in 93.7ms across 8,687 title embeddings via pgvector HNSW
- AI recursive self-improvement might not come so quickly after all dgellow · 69 pts · September 13, 2026 · 60% similar
- GPT‑Red: Unlocking Self-Improvement for Robustness alvis · 25 pts · July 15, 2026 · 55% similar
- The state of AI in 2026: On the road to ROI swolpers · 27 pts · August 25, 2026 · 55% similar
- AI researchers debate how close we are to recursive self-improvement artninja1988 · 85 pts · September 11, 2026 · 54% similar
- Overtraining as the path to human-like AI Brajeshwar · 16 pts · July 18, 2026 · 53% similar
Discussion Highlights (3 comments)
Taikhoom10
Yeah I think it is broadly applicable to tech as a whole, I mean any great startup is just really a counter positioned company to incumbents -
robotresearcher
Here’s a paper by Floreano at EPFL from 1997 explicitly on Red Queen dynamics for creating neural networks for intelligent robot control. There was lots of discussion of these ideas in the 1990s. In those days we trained very small NNs - tens of nodes - by evolving their weights and topologies. A run could take days on a workstation of the time. This particular paper is about co-evolving predator and prey, where the behavior of each is the ‘evaluation’ of the other. https://infoscience.epfl.ch/entities/publication/a65d0679-68...
richardfey
> "Instead of improving an agent against a fixed test, we let the evaluation evolve alongside the agent" This quote should have been highlighted earlier in the article.