LLMs are stuck in a groupthink groove. This startup is trying to get them out.

Mainstream LLMs converge on near-identical answers to open-ended prompts—ask ChatGPT or Claude for a random number and you'll almost always get 7. Australian startup Springboards built Flint, a model trained to produce wider response variety, like returning 3.7916 for that same prompt. A NeurIPS 2025 best paper found 25 different models mostly repeat 'time is a river' when asked for a metaphor. Springboards calls this 'lost information' and targets creative professionals who need to break out of the groupthink rut.

Why it matters: MIT Tech Review piece with a paper-backed finding on LLM homogenization and a named startup counter-model (Flint). Hits all three HKR axes. Score capped at 72 because the excerpt cuts off before any Flint benchmark or performance data — the claim is interesting but unverified ...