News from the frontier of AI forecasting

FORAXION, the company behind The Forecasting Machine, pushes the limits of actionable foresight.

Forecasts

2026-10-23The Forecasting Machine

The Forecasting Machine opens its 2026 U.S. Senate forecasts to the public

Explore The Forecasting Machine’s public Senate election forecasts, with race probabilities, chamber-control estimates and the reasoning behind each question.

2026-10-12The Forecasting Machine

Hypermind and The Forecasting Machine head to NEXTPredict New York

Émile Servan-Schreiber and Gilles Haumont announce NEXTPredict plans: a crowd-forecasting panel and demonstrations of Hypermind and The Forecasting Machine.

2026-10-09The Forecasting Machine

Hypermind relaunches its public prediction market with a new trading engine

Émile Servan-Schreiber announced Hypermind’s relaunch on 9 October 2026: free participation and cash rewards, with zero fees, adaptive liquidity and MECE order matching.

2026-10-09The Forecasting Machine

From worry to decision: Servan-Schreiber’s closing argument in Rijeka

At the Lürssen Foundation seminar in Rijeka, Émile Servan-Schreiber mapped the work around a forecast: defining the problem, shaping questions and making probabilities useful for a decision.

2026-10-08The Forecasting Machine

The Forecasting Machine Partners With Institut Montaigne on France’s 2027 Policy Choices

Institut Montaigne’s Les repères de Montaigne programme will use The Forecasting Machine’s probabilities to examine priority government actions after the 2027 election. The contribution belongs to the forthcoming 25th note, on the opening months of the next term.

2026-10-08The Forecasting Machine

Turning Signals Into Decisions: The Forecasting Machine at the OECD GFC Annual Meeting 2026

After two days at the OECD Government Foresight Community’s 2026 annual meeting, Gilles Haumont argued that foresight needs a faster route into institutional decisions. His account also points to the OECD’s existing use of The Forecasting Machine, alongside an earlier record of forecasting experiments and presentations.

2026-10-03The Forecasting Machine

Which 2027 Candidate Will Talk Digital Best? The Forecasting Machine’s First Campaign Forecasts on POL/N

On Delphine Sabattier’s POL/N podcast, Émile Servan-Schreiber presented The Forecasting Machine’s first forecasts on digital issues in France’s 2027 presidential race, from AI’s likely effect on the vote to Europe’s best chance of a real technology race, and debated them with Bernard Benhamou of the Institut de la souveraineté numérique.

2026-10-02The Forecasting Machine

Prediction Markets Explained: How to Read Polymarket Odds

What a prediction-market price means, why the resolution rules matter, and how to use Polymarket odds as evidence without mistaking them for certainty.

2026-10-02The Forecasting Machine

AI Forecasting vs Prediction Markets: How to Compare the Signals

Compare AI forecasts, Polymarket prices and human crowds on the same question, deadline and evidence cutoff. A practical guide to disagreement, evaluation and decision use.

2026-10-02The Forecasting Machine

Brier Score and Calibration: How to Measure Forecast Accuracy

Calculate a binary Brier score with worked examples, distinguish calibration from accuracy, and compare AI forecasts and prediction markets fairly.

2026-09-28The Forecasting Machine

Four lessons from 25 years of crowd forecasting: Servan-Schreiber at the Lürssen Foundation workshop

At a workshop convened by MIT’s Dražen Prelec in Rijeka on 1–2 October 2026, Émile Servan-Schreiber was scheduled to present four lessons on money, Brier scores, the Bayesian Truth Serum and AI forecasting.

2026-09-22The Forecasting Machine

Polls, Prediction Markets or AI? Servan-Schreiber and Verian’s Laure Salvaing on Reading France’s 2027 Election

In an Atlantico cross-interview, Émile Servan-Schreiber and pollster Laure Salvaing disagreed on what prediction markets measure and whether AI-simulated voters can replace real ones. A B SMART interview the same month added his view that, for forecasting at scale, AI has already won.