Laplace Research

Laplace Research builds forecasting models: systems that put calibrated probabilities on future events, and get scored on whether those probabilities hold up. We are named for Pierre-Simon Laplace, who gave us the first serious treatment of probability as a measure of what we don't know.

Our work centers on:

1. Training language models to produce calibrated probabilities rather than confident prose;
2. Building clean forecasting corpora — leakage detection, freeze-date splits, and auditing resolution quality at the source;
3. Reward design for post-training in domains where a forecast can be verifiably scored; and
4. Evaluation discipline: preregistration, correction for multiple comparisons, and publishing results that don't work.

Contact

• Web: laplaceresearch.org  ·  𝕏 @laplaceaires  ·  GitHub
• Arya Somu: aryasomu.com  ·  arya@laplaceresearch.org
• Bruce Nshuti Hirwa: brucenh.com  ·  bruce@laplaceresearch.org