Introducing Open Collider: an open-source engine that mechanically improves LLM creativity.
It generates non-trivial, high-quality ideas at scale, for any ideation problem.
LLMs collapse on the same ideas. Sample the same brief 100 times → most outputs land in the same place. Researchers call it the Artificial Hivemind (Jiang et al., 2025).
"Be more creative" moves the LLM's output by ~0.04 in embedding space.
Forcing structurally distant domain collisions moves it by ~0.28.
7× more. Same model, same brief.
So I built Open Collider: a pipeline based on the theory of bisociations (Koestler 1964), the same model that drives human creativity.
📊 Across 12 real-world ideation problems:
• 12/12 sign-test wins on embedding distance (p = .0002)
• 60%+ originality wins on 4,320 blind LLM-judge verdicts
• 4–13× further from the default cloud than "be original" prompts or longer context
• Idea relevance holds (win rate >50% on overall quality)
💻 Engine: first reply 👇
📝 Launch study: pinned tweet
Try it, Break it, Tell me what you find!
Cédric Lion@cdriclion