Research
Accurately simulating human beings requires new knowledge. Our research team's unique combination of experience in cognitive science, large language models, and human factors research has enabled SporeLogic to generate insights that have significantly improved our platforms ability to accurately simulate human beings across a variety of use cases
Model Convergence in LLM's
We've found that while LLM's are non-deterministic in their outputs, they do converge on a singular answer with repeated sampling.
From Tool -> Simulated Human
We've identified several techniques that override an LLM's general willigness to be a helpful tool and enable it to respond more accurately as if it were a human
Headline A/B Tests
We've found, just by simulating "human" as a demographic, our engine can accurately predict 75% of headline tests..
