News from the frontier of AI forecasting
FORAXION, the company behind The Forecasting Machine, pushes the limits of actionable foresight.
Results for “forecasting”
“Those markets are killed forever”: Servan-Schreiber on insider trading and the truth-machine problem
In an interview with Compliance+More on 15 September 2026, Émile Servan-Schreiber argued that suspected insider trading damages the product itself, not just compliance. It drives informed traders out of real-money prediction markets, and play money removes the incentive to rig outcomes.
Teaching students to forecast: Servan-Schreiber’s seminar at IE University and his class in the UM6P Executive MBA
A new run of “How to predict the future with collective and artificial intelligence” began at IE University on 14 September 2026, with students learning by forecasting in live prediction tournaments.
“Prediction People”: Servan-Schreiber on why money builds the business but not the forecast
In Stuart Crowley’s “Prediction People” interview, published on 24 August 2026, Émile Servan-Schreiber separated the forecasting mechanism from the business model. He also talked about forecasters who have kept playing for 25 years, AI competing with his own product, and why governments should use crowd forecasts.
A 2017 field guide to prediction markets for foresight, reread in 2026
Futuribles International has made Émile Servan-Schreiber’s 14-page toolbox on prediction markets free to download. Written in 2017 for foresight practitioners, its practical rules still hold, and its list of research frontiers reads differently now that AI forecasting exists.
“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.
Play money, same ballpark: Hypermind’s 12-year accuracy benchmark against Polymarket and Kalshi
Hypermind published the data from 1,141 play-money markets resolved since 2014 and compared them with Polymarket and Kalshi. The report concludes the three are at parity, and an independent commentator agreed that parity, not victory, is the defensible reading.
France 2027 on the Hypermind Market: How the Odds Moved Between Summer 2025 and Summer 2026
A year of Hypermind forecasts on the 2027 French presidential election, read as a market snapshot rather than a prediction: the RN’s combined chances rose, the “someone else” option shrank, and Édouard Philippe consolidated his position on the centre-right.
L’Express Interviews Émile Servan-Schreiber on Polymarket and Money-Free Forecasting
Days after France blocked Polymarket, L’Express interviewed Émile Servan-Schreiber, who argues that cash wagering is not what makes a crowd forecast accurate—and who described The Forecasting Machine’s all-AI system to the paper.
“There Is a Recipe for Collective Intelligence”: Servan-Schreiber’s Institut Diderot Lecture, Now in Print
The Institut Diderot has published the transcript of Émile Servan-Schreiber’s interactive lecture of 5 November 2025 on what makes groups smart, why consensus kills collective intelligence, and why AI still needs diverse human thinking.
