I built a prediction market that predicts itself
Clever self-referential loop, but novelty wears fast without deeper mechanics or payoff.

Free local AI for marketing models, but Weebly hosting undermines credibility.
Marketing analysts and data scientists
DataRobot · H2O.ai · RapidMiner
Link: https://modelfac1.weebly.com/
Try it out and any suggestion or feedback is welcome.
Why choose Modelfac? FREE: No licensing fees or subscriptions Standalone application: Install and run locally without relying on cloud infrastructure End-to-end workflow: From raw data to deployment ready models, and model documentation within a single application Propensity modeling and driver analysis: Build predictive models and identify key drivers behind customer behavior. Automatic model documentation: Generate template-based comprehensive model documentation with a single click. A/B testing and target list generation: Prepare campaign-ready treatment and control groups and export target lists for marketing and sales campaigns.
Clever self-referential loop, but novelty wears fast without deeper mechanics or payoff.
30M patent compounds indexed for protein target prediction in drug discovery.
This is a compact, dependency-free TestBed<MyModel> harness that forces models to predict next-step bitset inputs with deterministic seeds — clever for reproducible, low-level experimentation. Execution is pragmatic (header-only, quick compile, clear API), but there's no showcased model that actually passes the tests and the scope is deliberately narrow, so it’s more of a useful lab tool than a breakthrough benchmark.
Bet on AI clones of real people executing tasks in a sandboxed economy.
Agents trading prediction markets is novel, but core mechanics are unproven at scale.
Brier scoring and cross-asset correlations cut through prediction market noise.