News from the frontier of AI forecasting
FORAXION, the company behind The Forecasting Machine, pushes the limits of actionable foresight.
Results for “large language models”
“Performance = Expertise + Diversity”: Servan-Schreiber on the If This Then Dev Podcast
In an hour-long episode of the French developer podcast If This Then Dev, published on 12 August 2026, Émile Servan-Schreiber explained why groups need rules to be smart, how many novices it takes to match an expert, and why he sees large language models as collective intelligence.
“Supercollective Intelligence”: Servan-Schreiber’s 2018 book on crowds and prediction markets comes out in English
The English edition of Émile Servan-Schreiber’s “Supercollectif” is now on Amazon. He argues that ChatGPT and the rise of Polymarket since 2018 support, rather than overturn, the book’s case.
Crowds versus language models: the more accurate the AI forecaster, the more it errs like humans
A Philosophical Transactions B paper co-authored by Émile Servan-Schreiber compares 76 language-model setups with human crowds on 580 ForecastBench questions and finds evidence for the accuracy–correlation effect.
On B SMART, Servan-Schreiber Explains Why a Panel of AI Models Can Forecast Like a Panel of Experts
On B SMART’s Smart Tech on 2 March 2026, Émile Servan-Schreiber told Delphine Sabattier how The Forecasting Machine combines several language models into one sourced forecast, and why he sees those models as collective intelligence in their own right.
